numpy.insert () in Python



About:
numpy.insert (array, object, values, axis = none): inserts values ​​along the specified axis before the specified indices. 
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: removing from 1D array

# Python program illustrating
# numpy.insert ()

 

import numpy as geek

 
# Working on 1D

arr = geek.arange ( 5 )

print ( "1D arr:" , arr )

print ( "Shape:" , arr.shape)

  
# value = 9
# index = 1
# Insert before first index

a = geek.insert (arr, 1 , 9 )

print ( "Array after insertion:" , a)

print ( " Shape: " , a.shape)

 

 
# Working with 2D array

arr = geek.arange ( 12 ). reshape ( 3 , 4 )

print ( "2D arr:" , arr)

print ( "Shape:" , arr.shape)

 

a = geek.insert (arr, 1 , 9 , axis = 1 )

print ( "Array after insertion:" , a)

pri nt ( "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 program illustrating
# numpy.insert ()

 

import numpy as geek

  
# Working with 2D array

arr  = geek.arange ( 12 ). reshape ( 3 , 4 )

print ( "2D arr:" , arr)

print ( "Shape:" , arr.shape)

 
# Working with scalars

a = geek.insert (arr, [ 1 ], [[ 6 ], [ 9 ],], axis = 0

print ( "Array after insertion: " , a)

print ( "Shape:" , a.shape)

 
# Working with scalars

a = geek.insert (arr, [ 1 ] , [[ 8 ], [ 7 ], [ 9 ]], axis = 1 )

print ( "Array after insertion:" , 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: insert at different points

# Python program illustrating
# numpy.insert ()

 

import numpy as geek

 
# Working on 1D

arr = geek.arange ( 6 ). Reshape ( 2 , 3 )

print ( " 1D arr: " , arr)

print ( "Shape:" , arr.shape )

 
# value = 9
# index = 1
# Insert before the first index

a = geek.insert (arr, ( 2 , 4 ), 9 )

print ( "Insertion at two points:" , a)

print ( "Shape:" , a.shape)

 

  
# Working with 2D array

arr = geek.arange ( 12 ) .reshape ( 3 , 4 )

print ( "2D arr:" , arr)

print ( "Shape:" , arr.shape)

a = geek.insert (arr, ( 0 , 3 ), 66 , axis = 1 )

print ( "Insertion at two points:" , 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) 

Links:
https://docs.scipy.org/doc/numpy/reference/generated/numpy.insert.html#numpy.insert

Notes :
These codes will not work for online IDs. Please run them on your systems to see how they work.

This article is courtesy of Mohit Gupta_OMG