Numpy flipud() Function

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The Numpy flipud() function is used to reverse the order of elements in an array along the axis 0 (up/down). For a 2-D array, this flips the entries in each column in the up/down direction. Rows are preserved, but appear in a different order than before. This function is particularly useful for flipping the rows of an array for data manipulation or visualization purposes.

The function operates specifically along the up-down direction (reversing rows) while leaving other axes unchanged. The input array must have at least one dimension.

Syntax

Following is the syntax of the Numpy flipud() function −

numpy.flipud(m)  

Parameters

Following are the parameters of the Numpy flipud() function −

• m: The input array to be flipped. It must have at least one dimension.

Return Type

This function returns a view of the input array with its rows reversed. The original array remains unchanged.

Example

Following is a basic example of reversing the rows of a 2D array using the Numpy flipud() function −

import numpy as np  
my_array = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])  
print("Original Array:\n", my_array)  
result = np.flipud(my_array)  
print("Array after flipping rows:\n", result)  

Output

Following is the output of the above code −

Original Array:  
 [[1 2 3]  
  [4 5 6]  
  [7 8 9]]  
Array after flipping rows:  
 [[7 8 9]  
  [4 5 6]  
  [1 2 3]]  

Example: Flipping a 1D Array

The flipud() function also works for 1D arrays, effectively reversing their elements. Here, we have flipped 1D array −

import numpy as np  
my_array = np.array([10, 20, 30, 40])  
print("Original Array:", my_array)  
result = np.flipud(my_array)  
print("Reversed Array:", result)  

Output

Following is the output of the above code −

Original Array: [10 20 30 40]  
Reversed Array: [40 30 20 10]  

Example: Flipping a 3D Array

The flipud() function can also be applied to multi-dimensional arrays. Here, we have flipped the rows of a 3D array −

import numpy as np  
my_array = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])  
print("Original Array:\n", my_array)  
result = np.flipud(my_array)  
print("3D Array after flipping rows:\n", result)  

Output

Following is the output of the above code −

Original Array:  
 [[[1 2]  
   [3 4]]  

  [[5 6]  
   [7 8]]]  
3D Array after flipping rows:  
 [[[5 6]  
   [7 8]]  

  [[1 2]  
   [3 4]]]  

Example: Single-row Array

The flipud() function works for single-row arrays, though the operation does not alter the array −

import numpy as np  
my_array = np.array([[10, 20, 30, 40]])  
print("Original Array:\n", my_array)  
result = np.flipud(my_array)  
print("Array after flipping rows:\n", result)  

Output

Following is the output of the above code −

Original Array:  
 [[10 20 30 40]]  
Array after flipping rows:  
 [[10 20 30 40]]