NumPy stack()

Summary: in this tutorial, you’ll learn how to use the NumPy stack() function to join two or more arrays into a single array.

Introduction to the NumPy stack() function

The stack() function two or more arrays into a single array. Unlike the concatenate() function, the stack() function joins 1D arrays to be one 2D array and joins 2D arrays to be one 3D array.

The following shows the syntax of the stack() function:

numpy.stack((a1,a2,...),axis=0)Code language: Python (python)

In this syntax, the (a1, a2, …) is a sequence of arrays with ndarray type or array-like objects. All arrays a1, a2, .. must have the same shape.

The axis parameter specifies the axis in the result array along which the function stacks the input arrays. By default, the axis is zero which joins the input arrays vertically.

Besides the stack() function, NumPy also has vstack() function that joins two or more arrays vertically and hstack() function that joins two or more arrays horizontally.

NumPy stack() function examples

Let’s take some examples of using the stack() function.

1) Using stack() function to join 1D arrays

The following example uses the stack() function to join two 1D arrays:

import numpy as np

a = np.array([1, 2])
b = np.array([3, 4])

c = np.stack((a, b))
print(c)Code language: Python (python)

Output:

[[1 2] 
 [3 4]]Code language: Python (python)

The following example uses the stack() function to join two 1D arrays horizontally by using axis 1:

import numpy as np

a = np.array([1, 2])
b = np.array([3, 4])

c = np.stack((a, b), axis=1)
print(c)Code language: Python (python)

Output:

[[1 3] 
 [2 4]]Code language: Python (python)

2) Using numpy stack() function to join 2D arrays

The following example uses the stack() function to join elements of two 2D arrays. The result is a 3D array:

import numpy as np

a = np.array([
    [1, 2],
    [3, 4]
])
b = np.array([
    [5, 6],
    [7, 8]
])

c = np.stack((a, b))
print(c)
print(c.shape)Code language: Python (python)

Output:

[[[1 2]
  [3 4]]
 [[5 6]
  [7 8]]]
(2, 2, 2)Code language: Python (python)

NumPy stack() vs. concatenate()

The following example illustrates the difference between stack() and concatenate() functions:

a = np.array([1,2])
b = np.array([3,4])

c = np.concatenate((a,b)) # return 1-D array                    
d = np.stack((a,b)) # return 2-D array
print(c)
print(d)Code language: PHP (php)

Output:

[1 2 3 4]
[[1 2]
 [3 4]]Code language: JSON / JSON with Comments (json)

In this example, the concatenate() function joins elements of two arrays along an existing axis while the stack() function joins the two arrays along a new axis.

Summary

• Use the numpy stack() function to join two or more arrays into one.