Add|Append elements to Numpy array in Python(3 methods)

Numpy

In this post, we are going to learn about how to add|append elements to NumPy array in Python. by using append(), insert(), concatenate() function with help of python program examples

3 Methods to Add elements to Numpy array in Python


  • Numpy.append()
  • Numpy.insert()
  • Numpy.concatenate()

1. add| append element to Numpy array using append()


The Numpy appends() function adds an element in a NumPy array at the end of the array. This method does not modify the original array else returns a copy of the array after adding the passed element or array.

Syntax

numpy.append(arr,values,axis=none)

Parameters

  • arr: The copy of the array in which values are to be appended.
  • values: The values adding or append to array.The shape(size) must be same as arr exclude axis.If axis is not passed the value can be any shape and flatten before use.
  • axis: The axis represent adding values row-wise or columns-wise.if none both array or values are flatten before use.

Python Program to add element to NumPy array Using append()


import numpy as np


myarr = np.array([12,14,700,60,50])
numarr = np.array([3,6,9])
indexarr = [2,7]

#append an element at end of array


resarr = np.append(myarr, 90)
print('append an element in Numpy array: ', resarr)



#append array at end of array

resarr = np.append(myarr,numarr)
print('\n appended an Array in Numpy array: ', resarr)

Output

append an element in Numpy  array:  [ 12  14 700  60  50  90]

appended an Array in Numpy array :  [ 12  14 700  60  50   3   6   9]

2. add| append element to Numpy array using insert()


The Numpy library insert() function adds values in the numpy array along with the axis before the given indices.

Syntax

numpy.insert(arr,obj,values,axis=none)

Parameters

  • arr: The copy of the array in which values are to be appended.
  • obj :objects define index or indices before values inserted.
  • values :The values adding or append to array.The shape(size) must be same as arr exclude axis.If axis is not passed the value can be any shape and flatten before use.
  • axis: The axis represent adding values row-wise or columns-wise.if none both array or values are flatten before use.

Python Program to add element to NumPy array Using append()

import numpy as np 
arr = np.array([[10,12],[23,24],[15,16]])  

print ('The original array is flattened before insert.when axis is not passed')
result_arr = np.insert(arr,2,[10,20])

print(result_arr)

print ('\n The axis 0: is passed:') 
print (np.insert(arr,1,[45],axis = 0))


print ('\n The axis 1: is passed:\n') 
print (np.insert(arr,1,33,axis = 1))

Output

The original array is flattened before insert.when axis is not passed
[10 12 10 20 23 24 15 16]

 The axis 0: is passed:
[[10 12]
 [45 45]
 [23 24]
 [15 16]]

 The axis 1: is passed:

[[10 33 12]
 [23 33 24]
 [15 33 16]]

3.add|append element to Numpy array using concatenate()


The NumPy array concatenate() function concate two numpy array of same shape either row-wise or column-wise.This function by default concatenate arrays row-wise (axis=0).

Syntax

numpy.concatenate((a1, a2, ...an), axis=0, out=None, dtype=None)

Parameters

  • a1..an : The sequence of array_like object.The sequence must be of same shape
  • axis :The axis along which array is joined.It is optional parameter.
    • axis=none: The input array is flatten before use.
    • axis =1: The array is join column-wise
    • axis = 0 : The array is joined row-wise.It is defulat value of axis.
  • Out : optional The output ndarray if provided output is placed in this array.The shape must be correct.
  • dtype : optional if provided the output array of this type or str.

Python program to Add|append to Numpy array using concatenate()


import numpy as np


nparr1 = np.array([13, 14, 15, 18, 20])


nparr2 = np.array([22, 32, 33, 34, 36])


joined_nparr = np.concatenate( (nparr1, nparr2) )
print(joined_nparr)

Output

[13 14 15 18 20 22 32 33 34 36]

Python program to add|append 2D Numpy array using concatenate()

import numpy as np

nparr1 = np.array([[13, 14, 15],
                  [26, 12, 23],
                  [24, 25, 30]])

nparr2 = np.array([ [11, 54, 9],
                    [3, 6, 7],
                    [4, 8, 62]])
# Concatenate 2D np Arrays column wise
joined_nparr = np.concatenate( (nparr1, nparr2), axis=1 )

# Concatenate 2D np Arrays row-wise
join_nparr_rowwise = np.concatenate( (nparr1, nparr2), axis=0 )

print('concatenate column-wise:\n',joined_nparr)
print('\n concatenate row-wise:',join_nparr_rowwise)

Output

concatenate column-wise:
 [[13 14 15 11 54  9]
 [26 12 23  3  6  7]
 [24 25 30  4  8 62]]

 concatenate row-wise: [[13 14 15]
 [26 12 23]
 [24 25 30]
 [11 54  9]
 [ 3  6  7]
 [ 4  8 62]]

Summary

In this post, we have learned how to Add|Append elements to the Numpy array in Python with examples.