Let’s see how to mask an array in the Numpy Python library.

Let’s say we have an array in Numpy.

## How to use numpy mask?

Everything is OK except we need an additional mask for the given array. Let’s say I’d like to add a mask to see only elements of an array greater than 0.1.

First, let’s define the mask and see which elements are greater than 0.1.

import numpy as np random_array = np.random.random((1, 4)) print(random_array) mask = random_array > 0.1 print(mask)

Now you can see which items in an array are greater than 0.1.

## How to return elements matching the mask?

There is also the possibility to display only items that match the mask.

import numpy as np random_array = np.random.random((1, 4)) print(random_array) mask = random_array > 0.1 print(mask) print(random_array[mask])

Use random_array[mask] to print only the items that match the mask.

The mask works and only values greater than 0.1 are displayed.