Skip to content
Related Articles

Related Articles

How to append two NumPy Arrays?
  • Last Updated : 13 Jan, 2021

Prerequisites: Numpy

Two arrays in python can be appended in multiple ways and all possible ones are discussed below.

Method 1: Using append() method

This method is used to Append values to the end of an 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 :

A copy of array with values being appended at the end as per the mentioned object, along a given axis.

Example:

Python3




import numpy
  
  
array1 = numpy.array([1, 2, 3, 4, 5])
array2 = numpy.array([6, 7, 8, 9, 10])
  
# Appending both arrays using Append method
array1 = numpy.append(array1, array2)
print(array1)

 Output:

[ 1  2  3  4  5  6  7  8  9 10]

Method 2: Using concatenate() method

Concatenate method Joins a sequence of arrays along an existing axis.



Syntax : 

numpy.concatenate((arr1, arr2, …), axis=0, out=None)
 

Parameters :

  • arr1, arr2, … : [sequence of array_like] The arrays must have the same shape, except in the dimension corresponding to axis.
  • axis : [int, optional] The axis along which the arrays will be joined. If axis is None, arrays are flattened before use. Default is 0.
  • out : [ndarray, optional] If provided, the destination to place the result. The shape must be correct, matching that of what concatenate would have returned if no out argument were specified.

Return : [ndarray] The concatenated array.

Example:

Python3




import numpy
  
  
array1 = numpy.array([1, 2, 3, 4, 5])
array2 = numpy.array([6, 7, 8, 9, 10])
  
# Appending both Arrays using concatenate() method.
array1 = numpy.concatenate([array1, array2])
print(array1)

Output:

[ 1  2  3  4  5  6  7  8  9 10]

Method 3: Using stack() method

Stack method Joins a sequence of arrays along a new axis.

Syntax : numpy.stack(arrays, axis)

Parameters :
 

  • arrays : [array_like] Sequence of arrays of the same shape.
  • axis : [int] Axis in the resultant array along which the input arrays are stacked.

Return : [stacked ndarray] The stacked array of the input arrays which has one more dimension than the input arrays.

Example:

Python3




import numpy
  
  
array1 = numpy.array([1, 2, 3, 4, 5])
array2 = numpy.array([6, 7, 8, 9, 10])
  
# Join a sequence of arrays along a new axis.
array1 = numpy.stack([array1, array2])
print(array1)

Output:

[[ 1  2  3  4  5]

 [ 6  7  8  9 10]]

Method 4: Using hstack() method

hstack method Stacks arrays in sequence horizontally (column wise).

Syntax : numpy.hstack(tup)

Parameters :
 

  • tup : [sequence of ndarrays] Tuple containing arrays to be stacked. The arrays must have the same shape along all but the second axis.

Return : [stacked ndarray] The stacked array of the input arrays.

Example:

Python3




import numpy
  
  
array1 = numpy.array([1, 2, 3, 4, 5])
array2 = numpy.array([6, 7, 8, 9, 10])
  
# Stack arrays in sequence horizontally (column wise).
array1 = numpy.hstack([array1, array2])
print(array1)

Output:

[ 1  2  3  4  5  6  7  8  9 10]

Method 5: Using vstack() method

vstack method Stacks arrays in sequence vertically (row wise).

Syntax : numpy.vstack(tup)

Parameters :
 

  • tup : [sequence of ndarrays] Tuple containing arrays to be stacked. The arrays must have the same shape along all but the first axis.

Return : [stacked ndarray] The stacked array of the input arrays.

Example:

Python3




import numpy
  
  
array1 = numpy.array([1, 2, 3, 4, 5])
array2 = numpy.array([6, 7, 8, 9, 10])
  
# Stack arrays in sequence vertically (row wise).
array1 = numpy.vstack([array1, array2])
print(array1)

Output:

[[ 1  2  3  4  5]

 [ 6  7  8  9 10]]

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

My Personal Notes arrow_drop_up
Recommended Articles
Page :