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Appending values at the end of an NumPy array
  • Last Updated : 02 Sep, 2020

Let us see how to append values at the end of a NumPy array. Adding values at the end of the array is a necessary task especially when the data is not fixed and is prone to change. For this task we can use numpy.append(). This function can help us to append a single value as well as multiple values at the end of the array.

Syntax : numpy.append(array, values, axis = None)
Parameters :

  • array : Input array.
  • values : values to be added in the array.
  • axis : Axis along which we want to insert the values.

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

Examples 1 : Appending a single value to a 1D array. For 1D array, using the axis argument is not necessary as the array is flattened by default.

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# importing the module
import numpy as np
  
# creating an array
arr = np.array([1, 8, 3, 3, 5])
print('Original Array : ', arr)
  
# appending to the array
arr = np.append(arr, [7])
print('Array after appending : ', arr)

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Output :



Original Array :  [1 8 3 3 5]
Array after appending :  [1 8 3 3 5 7]

Example 2 : Appending another array at the end of 1D array. You may pass a list or an array to the append function, the result will be the same.

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# importing the module
import numpy as np
  
# creating an array
arr1 = np.array([1, 2, 3])
print('First array is : ', arr1)
  
# creating another array
arr2 = np.array([4, 5, 6])
print('Second array is : ', arr2)
  
# appending arr2 to arr1
arr = np.append(arr1, arr2)
print('Array after appending : ', arr)

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Output :

First array is :  [1 2 3]
Second array is :  [4 5 6]
Array after appending :  [1 2 3 4 5 6]

Example 3 : Appending values at the end of the n-dimensional array. It is important that the dimensions of both the array matches otherwise it will give an error.

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# importing the module
import numpy as np
  
# create an array
arr = np.arange(1, 13).reshape(2, 6)
print('Original Array')
print(arr, '\n')
  
# create another array which is
# to be appended column-wise
col = np.arange(5, 11).reshape(1, 6)
print('Array to be appended column wise')
print(col)
arr_col = np.append(arr, col, axis = 0)
print('Array after appending the values column wise')
print(arr_col, '\n')
  
# create an array which is
# to be appended row wise
row = np.array([1, 2]).reshape(2, 1)
print('Array to be appended row wise')
print(row)
arr_row = np.append(arr, row, axis = 1)
print('Array after appending the values row wise')
print(arr_row)

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Output :

Original Array
[[ 1  2  3  4  5  6]
 [ 7  8  9 10 11 12]] 

Array to be appended column wise
[[ 5  6  7  8  9 10]]
Array after appending the values column wise
[[ 1  2  3  4  5  6]
 [ 7  8  9 10 11 12]
 [ 5  6  7  8  9 10]] 

Array to be appended row wise
[[1]
 [2]]
Array after appending the values row wise
[[ 1  2  3  4  5  6  1]
 [ 7  8  9 10 11 12  2]]

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