Vertically split numpy array with vsplit()

In this tutorial, we will look at the numpy vsplit() function and its usage with the help of some examples.

What is does numpy vsplit() do?

numpy array split row-wise with numpy vsplit()

The numpy vsplit() function is used to split a numpy array into multiple sub-arrays vertically (row-wise). Pass the input array and the number of sub-arrays as arguments. The following is the syntax:

import numpy as np

# split array row-wise (vertically)
sub_arrays = np.vsplit(arr, indices_or_sections)

It returns a list of numpy arrays created from the split (the sub-arrays).

Let’s look at some examples of using the numpy vsplit() function.

Vertically split a 2d numpy array

Let’s split a 2d array of shape (4, 3) at the middle into two sub-arrays of shape (2, 3) each.

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import numpy as np

# create a 2d numpy array
arr = np.array([[1, 2, 2],
                [2, 0, 0],
                [3, 1, 1],
                [4, 0, 4]])
# split the array into 2 subarrays vertically
sub_arrays = np.vsplit(arr, 2)
# display the sub_arrays
sub_arrays

Output:

[array([[1, 2, 2],
        [2, 0, 0]]),
 array([[3, 1, 1],
        [4, 0, 4]])]

You can see that the input array of shape (4, 3) has been split into two halves row-wise (vertically) with subarrays of shape (2, 3).

Let’s now split the same input array into 4 sub-arrays of (1, 3) by splitting all the rows.

# create a 2d numpy array
arr = np.array([[1, 2, 2],
                [2, 0, 0],
                [3, 1, 1],
                [4, 0, 4]])
# split the array into 4 subarrays vertically
sub_arrays = np.vsplit(arr, 4)
# display the sub_arrays
sub_arrays

Output:

[array([[1, 2, 2]]),
 array([[2, 0, 0]]),
 array([[3, 1, 1]]),
 array([[4, 0, 4]])]

We get four (1, 3) sub-arrays.

Using numpy split() with axis=0

Alternatively, you can perform a vertical split with the numpy split() function. Just pass axis=0 along with the input array and the number of sections to split it into.

Let’s split the above 2d array into two sub-arrays vertically but using the numpy split() function this time.

# create a 2d numpy array
arr = np.array([[1, 2, 2],
                [2, 0, 0],
                [3, 1, 1],
                [4, 0, 4]])
# split the array into 2 subarrays vertically
sub_arrays = np.split(arr, 2, axis=0)
# display the sub_arrays
sub_arrays

Output:

[array([[1, 2, 2],
        [2, 0, 0]]),
 array([[3, 1, 1],
        [4, 0, 4]])]

We get the same result as we did with the vsplit() function.

For more on the numpy vsplit() function, refer to its documentation.

With this, we come to the end of this tutorial. The code examples and results presented in this tutorial have been implemented in a Jupyter Notebook with a python (version 3.8.3) kernel having numpy version 1.18.5

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Author

Piyush Raj

Piyush is a data professional passionate about using data to understand things better and make informed decisions. He has experience working as a Data Scientist in the consulting domain and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.

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