{"id":5872,"date":"2021-05-16T10:43:41","date_gmt":"2021-05-16T05:13:41","guid":{"rendered":"https:\/\/python-programs.com\/?p=5872"},"modified":"2021-11-22T18:42:37","modified_gmt":"2021-11-22T13:12:37","slug":"how-to-reverse-a-1d-2d-numpy-array-using-np-flip-and-operator-in-python","status":"publish","type":"post","link":"https:\/\/python-programs.com\/how-to-reverse-a-1d-2d-numpy-array-using-np-flip-and-operator-in-python\/","title":{"rendered":"How to Reverse a 1D & 2D numpy array using np.flip() and [] operator in Python"},"content":{"rendered":"
By not passing any start or end parameter, so by default complete array is picked. And as step size is -1, so elements selected from last to first.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# Creating a numpy array\r\nnum_arr = sc.array([11,22,33,44,55,66])\r\n\r\nprint('Original Array: ',num_arr)\r\n\r\n# To get reverse of numpy array\r\nrev_arr = num_arr[::-1]\r\n\r\nprint('Reversed Array : ', rev_arr)<\/pre>\nOutput :\r\nOriginal Array:\u00a0 [11 22 33 44 55 66]\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \r\nReversed Array :\u00a0 [66 55 44 33 22 11]<\/pre>\nReverse Array is View Only :<\/h3>\n
Here if we do any modification in reversed array, it will also be reflected in original array.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# Creatin a numpy array\r\nnum_arr = sc.array([11,22,33,44,55,66])\r\n\r\n# To get reverse of numpy array\r\nrev_arr = num_arr[::-1]\r\nrev_arr[4]=63\r\n\r\nprint('Modified reversed Array : ', rev_arr)\r\nprint('Original array is: ',num_arr)<\/pre>\nOutput :\r\nModified reversed Array :\u00a0 [66 55 44 33 63 11]\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \r\nOriginal array is:\u00a0 [11 63 33 44 55 66]<\/pre>\nReverse Numpy array using np.flip() :<\/h3>\n
flip()<\/code> function provided by Python’s numpy module helps to flip or reverse the content of numpy array.<\/p>\n
Syntax : numpy.flip(arr, axis=None)<\/pre>\nwhere,<\/p>\n
\n
- arr :<\/strong>\u00a0 A numpy array<\/li>\n
- axis :<\/strong> Axis along which contents need to be flipped. If
None<\/code>, contents will be flipped along axis of array.<\/li>\n<\/ul>\n
Reverse 1D Numpy array using np.flip() :<\/h3>\n
Here as it is 1 -D Numpy array, there is no need of axis parameter.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# To create a Numpy array\r\nnum_arr = sc.array([11,22,33,44,55])\r\n\r\nprint('Original array: ',num_arr)\r\n\r\n# To get reverse of numpy array\r\nrev_arr = sc.flip(num_arr)\r\n\r\nprint('Reversed Array is : ', rev_arr)<\/pre>\nOutput :\r\nOriginal array:\u00a0 [11 22 33 44 55]\r\nReversed Array is :\u00a0 [55 44 33 22 11]<\/pre>\nReverse 2D Numpy Array using np.flip() :<\/h3>\n
Reverse contents in all rows and all columns of 2D Numpy Array :<\/h4>\n
Here we don’t provide parameter in
np.flip()<\/code> function, then contents will be reversed along the axes of 2-D Numpy array.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# to create a 2D Numpy array\r\ntwoD_Arr = sc.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\r\n\r\nprint('Original Array is: ',twoD_Arr)\r\n\r\n# to reverse 2D numpy array\r\nrev_Arr = sc.flip(twoD_Arr)\r\n\r\nprint('Reversed Array : ')\r\nprint(rev_Arr)<\/pre>\nOutput :\r\nOriginal Array is:\r\n[[1 2 3]\r\n[4 5 6]\r\n[7 8 9]]\r\nReversed Array :\r\n[[9 8 7]\r\n[6 5 4]\r\n[3 2 1]]<\/pre>\nReverse contents of all rows only in 2D Numpy Array :<\/h4>\n
If we provide axix parameter i.e.
axis=1<\/code>, then rows of array will be reversed.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# to create a 2D Numpy array\r\ntwoD_Arr = sc.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\r\n\r\nprint('Original Array is: ',twoD_Arr)\r\n\r\n# to reverse the content of each row in array\r\nrev_Arr = sc.flip(twoD_Arr, axis=1)\r\n\r\nprint('Reversed Array : ')\r\nprint(rev_Arr)<\/pre>\nOutput :\r\nOriginal Array is:\u00a0 [[1 2 3]\r\n[4 5 6]\r\n[7 8 9]]\r\nReversed Array :\r\n[[3 2 1]\r\n[6 5 4]\r\n[9 8 7]]<\/pre>\nReverse contents of all columns only in 2D Numpy Array :<\/h4>\n
If we provide axix parameter i.e.
axis=0<\/code>, then rows of array will be reversed.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# to create a 2D Numpy array\r\ntwoD_Arr = sc.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\r\n\r\nprint('Original Array is: ',twoD_Arr)\r\n\r\n# to reverse the content of each column in array\r\nrev_Arr = sc.flip(twoD_Arr, axis=0)\r\n\r\nprint('Reversed Array : ')\r\nprint(rev_Arr)<\/pre>\nOutput :\r\nOriginal Array is:\r\n[[1 2 3]\r\n[4 5 6]\r\n[7 8 9]]\r\nReversed Array :\r\n[[7 8 9]\r\n[4 5 6]\r\n[1 2 3]]<\/pre>\nReverse contents of only one row in 2D Numpy Array :<\/h4>\n
Let, we want to reverse only 1st row of a Numpy array.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# to create a 2D Numpy array\r\ntwoD_Arr = sc.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\r\n\r\nprint('Original Array is: ',twoD_Arr)\r\n\r\n# to reverse only 1st row\r\ntwoD_Arr[0] = sc.flip(twoD_Arr[0])\r\n\r\nprint('Reversed Array : ')\r\nprint(twoD_Arr)<\/pre>\nOutput :\r\nOriginal Array is:\r\n[[1 2 3]\r\n[4 5 6]\r\n[7 8 9]]\r\nReversed Array :\r\n[[3 2 1]\r\n[4 5 6]\r\n[7 8 9]]<\/pre>\nReverse contents of only one column in 2D Numpy Array :<\/h4>\n
Let, we want to reverse only 3rd column of a Numpy array.<\/p>\n
# Program :\r\n\r\nimport numpy as sc\r\n\r\n# to create a 2D Numpy array\r\ntwoD_Arr = sc.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\r\n\r\nprint('Original Array is: ',twoD_Arr)\r\n\r\n# to reverse the content of 3rd column in array\r\ntwoD_Arr[:,2] = sc.flip(twoD_Arr[:,2])\r\n\r\nprint('Reversed Array : ')\r\nprint(twoD_Arr)<\/pre>\nOutput :\r\nOriginal Array is:\r\n[[1 2 3]\r\n[4 5 6]\r\n[7 8 9]]\r\nReversed Array :\r\n[[1 2 9]\r\n[4 5 6]\r\n[7 8 3]]<\/pre>\n<\/p>\n","protected":false},"excerpt":{"rendered":"
Reversing a 1D and 2D numpy array using np.flip() and [] operator in Python. Reverse 1D Numpy array using ‘[]’ operator : By not passing any start or end parameter, so by default complete array is picked. And as step size is -1, so elements selected from last to first. # Program : import numpy …<\/p>\n