numpy.append() in Python

The numpy.append() appends values along the mentioned axis at the end of the array Syntax : 

numpy.append(array, values, axis = None)

Parameters : 

array   : [array_like]Input array. 
values  : [array_like]values to be added in the arr. Values should be 
     shaped so that arr[...,obj,...] = values. If the axis is defined values can be of any
     shape as it will be flattened before use.
axis    : Axis along which we want to insert the values. By default, array
     is flattened.    

Return : 

An copy of array with values being appended at the end as per the mentioned object
along a given axis. 

Code 1 : Appending arrays

Python

# Python Program illustrating
# numpy.append()

import numpy as geek

#Working on 1D
arr1 = geek.arange(5)
print("1D arr1 : ", arr1)
print("Shape : ", arr1.shape)


arr2 = geek.arange(8, 12)
print("\n1D arr2 : ", arr2)
print("Shape : ", arr2.shape)


# appending the arrays
arr3 = geek.append(arr1, arr2)
print("\nAppended arr3 : ", arr3)

Output : 

1D arr1 :  [0 1 2 3 4]
Shape :  (5,)

1D arr2 :  [ 8  9 10 11]
Shape :  (4,)

Appended arr3 :  [ 0  1  2  3  4  8  9 10 11]

The time complexity of the numpy.append() function is O(n) where n is the number of elements being appended. This means that the time needed to append elements increases linearly with the number of elements being appended.

The space complexity of the numpy.append() function is also O(n) where n is the number of elements being appended. This means that the amount of space needed to append elements increases linearly with the number of elements being appended.

Code 2 : Playing with axis

Python

# Python Program illustrating
# numpy.append()

import numpy as geek

#Working on 1D
arr1 = geek.arange(8).reshape(2, 4)
print("2D arr1 : \n", arr1)
print("Shape : ", arr1.shape)


arr2 = geek.arange(8, 16).reshape(2, 4)
print("\n2D arr2 : \n", arr2)
print("Shape : ", arr2.shape)


# appending the arrays
arr3 = geek.append(arr1, arr2)
print("\nAppended arr3 by flattened : ", arr3)

# appending the arrays with axis = 0
arr3 = geek.append(arr1, arr2, axis = 0)
print("\nAppended arr3 with axis 0 : \n", arr3)

# appending the arrays with axis = 1
arr3 = geek.append(arr1, arr2, axis = 1)
print("\nAppended arr3 with axis 1 : \n", arr3)

Output : 

2D arr1 : 
 [[0 1 2 3]
 [4 5 6 7]]
Shape :  (2, 4)

2D arr2 : 
 [[ 8  9 10 11]
 [12 13 14 15]]
Shape :  (2, 4)

Appended arr3 by flattened :  [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15]

Appended arr3 with axis 0 : 
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]
 [12 13 14 15]]

Appended arr3 with axis 1 : 
 [[ 0  1  2  3  8  9 10 11]
 [ 4  5  6  7 12 13 14 15]]

References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.append.html#numpy.append . This article is contributed by Mohit Gupta_OMG 😀. If you like GeeksforGeeks and would like to contribute, you can also write an article using write.geeksforgeeks.org or mail your article to review-team@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.