The numpy.insert() function inserts values along the mentioned axis before the given indices. Syntax :
numpy.insert(array, object, values, axis = None)
Parameters :
array : [array_like]Input array. object : [int, array of ints]Sub-array with the index or indices before which values is inserted values : [array_like]values to be added in the arr. Values should be shaped so that arr[...,obj,...] = values. If the type of values is different from that of arr, values is converted to the type of arr axis : Axis along which we want to insert the values. By default, it object is applied to flattened array
Return :
An copy of array with values being inserted as per the mentioned object along a given axis.
Code 1 : Deletion from 1D array
Python
# Python Program illustrating # numpy.insert() import numpy as geek #Working on 1D arr = geek.arange( 5 ) print (" 1D arr : \n", arr) print ("Shape : ", arr.shape) # value = 9 # index = 1 # Insertion before first index a = geek.insert(arr, 1 , 9 ) print ("\nArray after insertion : ", a) print ("Shape : ", a.shape) # Working on 2D array arr = geek.arange( 12 ).reshape( 3 , 4 ) print ("\n\n2D arr : \n", arr) print ("Shape : ", arr.shape) a = geek.insert(arr, 1 , 9 , axis = 1 ) print ("\nArray after insertion : \n", a) print ("Shape : ", a.shape) |
Output :
1D arr : [0 1 2 3 4] Shape : (5,) Array after insertion : [0 9 1 2 3 4] Shape : (6,) 2D arr : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Shape : (3, 4) Array after insertion : [[ 0 9 1 2 3] [ 4 9 5 6 7] [ 8 9 9 10 11]] Shape : (3, 5)
Code 2 : Working with Scalars
Python
# Python Program illustrating # numpy.insert() import numpy as geek # Working on 2D array arr = geek.arange( 12 ).reshape( 3 , 4 ) print (" 2D arr : \n", arr) print ("Shape : ", arr.shape) # Working with Scalars a = geek.insert(arr, [ 1 ], [[ 6 ],[ 9 ],], axis = 0 ) print ("\nArray after insertion : \n", a) print ("Shape : ", a.shape) # Working with Scalars a = geek.insert(arr, [ 1 ], [[ 8 ],[ 7 ],[ 9 ]], axis = 1 ) print ("\nArray after insertion : \n", a) print ("Shape : ", a.shape) |
Output :
2D arr : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Shape : (3, 4) Array after insertion : [[ 0 1 2 3] [ 6 6 6 6] [ 9 9 9 9] [ 4 5 6 7] [ 8 9 10 11]] Shape : (5, 4) Array after insertion : [[ 0 8 1 2 3] [ 4 7 5 6 7] [ 8 9 9 10 11]] Shape : (3, 5)
Code 3 : Insertion at different points
Python
# Python Program illustrating # numpy.insert() import numpy as geek #Working on 1D arr = geek.arange( 6 ).reshape( 2 , 3 ) print (" 1D arr : \n", arr) print ("Shape : ", arr.shape) # value = 9 # index = 1 # Insertion before first index a = geek.insert(arr, ( 2 , 4 ), 9 ) print ("\nInsertion at two points : ", a) print ("Shape : ", a.shape) # Working on 2D array arr = geek.arange( 12 ).reshape( 3 , 4 ) print ("\n\n2D arr : \n", arr) print ("Shape : ", arr.shape) a = geek.insert(arr, ( 0 , 3 ), 66 , axis = 1 ) print ("\nInsertion at two points : \n", a) print ("Shape : ", a.shape) |
Output :
1D arr : [[0 1 2] [3 4 5]] Shape : (2, 3) Insertion at two points : [0 1 9 2 3 9 4 5] Shape : (8,) 2D arr : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Shape : (3, 4) Insertion at two points : [[66 0 1 2 66 3] [66 4 5 6 66 7] [66 8 9 10 66 11]] Shape : (3, 6)
References : https://docs.scipy.org/doc/numpy/reference/generated/numpy.insert.html#numpy.insert Note : These codes won’t run on online IDE’s. Please run them on your systems to explore the working. This article is contributed by Mohit Gupta_OMG 😀. If you like Lazyroar 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 Lazyroar 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.