numpy.append() in Python
Last Updated :
07 Mar, 2024
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
import numpy as geek
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)
arr3 = geek.append(arr1, arr2)
print("\nAppended arr3 : ", arr3)
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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
import numpy as geek
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)
arr3 = geek.append(arr1, arr2)
print("\nAppended arr3 by flattened : ", arr3)
arr3 = geek.append(arr1, arr2, axis = 0)
print("\nAppended arr3 with axis 0 : \n", arr3)
arr3 = geek.append(arr1, arr2, axis = 1)
print("\nAppended arr3 with axis 1 : \n", arr3)
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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]]
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