How to Use NumPy vstack() in Python

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  • Post category:NumPy / Python
  • Post last modified:November 22, 2023
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The NumPy vstack() function in Python is used to vertically(row-wise) stack arrays. It takes a sequence of arrays as input and stacks them vertically to create a new array. The arrays must have the same number of columns. It takes all elements from the given arrays and forms a single array, where the elements are added vertically. This process is similar to the concatenation of arrays along the default axis=0 after concatenating 1-D arrays of shape (N,) turn into reshaping (1, N).

It has only one parameter i.e. tuple of arrays. You can use vstack() very effectively up to three-dimensional arrays. In this article, I will explain numpy.vstack() function and use its syntax, parameters, and how you can create a single array by taking elements of one or more arrays.

1. Quick Examples of NumPy vstack() Function

If you are in a hurry, below are some quick examples of how to use vstack() function.


# Quick examples of numpy vstack() function

# Example 1 : Using vstack() 
# Get the stacked array
arr = np.array([1, 2, 3])
arr1 = np.array([4, 5, 6])
arr2 = np.vstack((arr, arr1))

# Example 2 : Get the stacked array 
arr = np.array([[1], [2], [3]])
arr1 = np.array([[4], [5], [6]])
arr2 = np.array([[7], [8], [9]])
arr3 = np.vstack((arr, arr1, arr2))

# Example 3 : Get the stacked array 
arr = np.array([[1], [2], [3]])
arr1 = np.array([[4], [5], [6]])
arr2 = np.array([[7], [8], [9]])
arr3 = np.vstack((arr, arr1, arr2))

# Example 4 : Get the 3-D stacked array
arr = np.array([[[1, 3], [2, 4]], [[3, 5], [5, 7]]])
arr1 = np.array([[[4, 1], [5, 7]], [[6, 8],[3, 5]]])
arr2 = np.vstack((arr, arr1))

2. Syntax of NumPy vstack()

Following is the syntax of the vstack() function.


# Syntax of vstack() 
numpy.vstack(tup)

2.1 Parameters of the vstack()

Following is the parameter of the NumPy vstack().

tup : tuple of ndarrays – The arrays to be stacked vertically. The arrays must have the same number of columns (i.e., the size of the second axis).

2.2 Return Value of the vstack()

Stacked ndarray: The vertically stacked array formed by concatenating the input arrays.

3. Usage of the NumPy vstack()

The vstack() function in NumPy is used specifically to vertically stack, or concatenate, a sequence of NumPy arrays along the vertical axis (axis=0). This results in a single array where the data from the input arrays is stacked vertically. Python NumPy module provides different types of functions which are concatenate(), stack(), vstack(), and hstack().

Below I have provided an image explaining how vstack works, it will give you better understanding.

NumPy vstack
numpy.vstack()

Let’s create 1-D arrays using numpy.array() and apply this function, it will return the stacked array., where the elements are stacked row-wise.

You can create two 1D NumPy arrays, arr and arr1, and then uses the numpy.vstack() function to vertically stack them into a 2D array, arr2.


# Import numpy
import numpy as np

# Create input array
arr = np.array([1, 2, 3])
print("First array:\n",arr) 
arr1 = np.array([4, 5, 6])
print("Second array:\n",arr1) 

# Using vstack() function
# Get the stacked array
arr2 = np.vstack((arr, arr1))
print("Stacked array:\n",arr2) 

Yields below output.

NumPy vstack

As you can see, the np.vstack() function has combined the two 1D arrays arr and arr1 into a 2D array, arr2, by stacking them vertically. Each original array becomes a row in the resulting 2D array.

4. Get the 2-D Stacked NumPy Array

You are creating two 2D NumPy arrays, arr and arr1, and then using the np.vstack() function to vertically stack them into a new 2D array, arr2.


# Create 2D array
arr = np.array([[1, 2], [3, 4]])
arr1 = np.array([[4, 5], [6, 7]]) 

# Get the stacked array
arr2 = np.vstack((arr, arr1))
print("Stacked 2D array:\n",arr2) 

# Output:
# Stacked 2D array:
#  [[1 2]
#  [3 4]
#  [4 5]
#  [6 7]]

This time you will pass three 2-D NumPy arrays into this function, it will return the 2-D single array where the elements are stacked vertically.

To create three 2D NumPy arrays, arr, arr1, and arr2, each containing single-column vectors. Then, you’re using the np.vstack() function to vertically stack them into a new 2D array, arr3.


# Create input array
arr = np.array([[1], [2], [3]])
arr1 = np.array([[4], [5], [6]])
arr2 = np.array([[7], [8], [9]])

# Get the stacked array
arr3 = np.vstack((arr, arr1, arr2))
print("Stacked 2D single array:\n",arr3)

# Output:
# Stacked 2D single array:
# [[1]
# [2]
# [3]
# [4]
# [5]
# [6]
# [7]
# [8]
# [9]]

5. Get the 3-D Stacked NumPy Array

You can pass 3-D NumPy arrays as a parameter into this function, it will return a single array. Let’s take two 3-D arrays of shapes (2, 2, 2) and apply this function, it will return a single 3-D array of shapes (4, 2, 2). For example,


# Create 3D arrays
arr = np.array([[[1, 3], [2, 4]], [[3, 5], [5, 7]]])
arr1 = np.array([[[4, 1], [5, 7]], [[6, 8],[3, 5]]])

# Get the 3-D stacked array
arr2 = np.vstack((arr, arr1))
print("Stacked 3D array:\n",arr2) 

Yields below output


# Output:
Stacked 3D array:
 [[[1 3]
  [2 4]]

 [[3 5]
  [5 7]]

 [[4 1]
  [5 7]]

 [[6 8]
  [3 5]]]

Frequently Asked Questions

What does numpy.vstack() do?

The numpy.vstack() function in NumPy is used to vertically stack or concatenate arrays along the vertical axis (axis=0). It takes a sequence of arrays and stacks them vertically, forming a new array.

Can I stack more than two arrays?

The numpy.vstack() function is flexible and allows you to stack more than two arrays. You can pass any number of arrays as a tuple to numpy.vstack().

Can I use numpy.vstack() with 1D arrays?

you can use numpy.vstack() with 1D arrays as well. When you use it with 1D arrays, they will be treated as if they are 2D arrays with a single column. The resulting stacked array will be a 2D array.

Can I vertically stack arrays with different data types?

You can vertically stack arrays with different data types using numpy.vstack(). When you vertically stack arrays with different data types, NumPy will attempt to promote them to a common data type that can accommodate all the data without loss of information.

Is there an alternative to numpy.vstack()?

An alternative to numpy.vstack() is numpy.concatenate() when you want to vertically stack arrays along the 0-axis (rows).

How do I vertically stack three 2D arrays?

To vertically stack three 2D NumPy arrays, you can use the numpy.vstack() function.

Conclusion

In this article, I have explained numpy.vstack() and using this how you can stack the sequence of given arrays into a single array with examples.

References

Vijetha

Vijetha is an experienced technical writer with a strong command of various programming languages. She has had the opportunity to work extensively with a diverse range of technologies, including Python, Pandas, NumPy, and R. Throughout her career, Vijetha has consistently exhibited a remarkable ability to comprehend intricate technical details and adeptly translate them into accessible and understandable materials. Follow me at Linkedin.

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