The Numpy library in Python comes with a number of useful functions and methods to work with and manipulate the data in arrays. In this tutorial, we will look at how to get all the even elements from a Numpy array with the help of some examples.
Steps to get all the even values in Numpy array
You can use boolean indexing to filter the Numpy array such that the resulting array contains only the elements that specify a given condition. For example, values that are even.
Step 1 – Create a Numpy array
First, we will create a Numpy array that we will be using throughout this tutorial.
import numpy as np # create a numpy array ar = np.array([1, 2, 3, 4, 5, 6, 7, 8]) # display the array print(ar)
Output:
[1 2 3 4 5 6 7 8]
Here, we used the numpy.array()
function to create a one-dimensional Numpy array containing some numbers.
Step 2 – Filter the array for even values using a boolean expression
To get all the even elements of a Numpy array, filter the array using boolean indexing.
Here, we will specify our boolean expression, ar % 2 == 0
and then use the boolean array resulting from this expression to filter our original array. The %
(modulus) operator returns the remainder when the left value is divided by the right value. Since even numbers are divisible by 2, ar % 2
will result in 0 if the number is even.
Let’s get all the even elements in the array created above
Introductory ⭐
- Harvard University Data Science: Learn R Basics for Data Science
- Standford University Data Science: Introduction to Machine Learning
- UC Davis Data Science: Learn SQL Basics for Data Science
- IBM Data Science: Professional Certificate in Data Science
- IBM Data Analysis: Professional Certificate in Data Analytics
- Google Data Analysis: Professional Certificate in Data Analytics
- IBM Data Science: Professional Certificate in Python Data Science
- IBM Data Engineering Fundamentals: Python Basics for Data Science
Intermediate ⭐⭐⭐
- Harvard University Learning Python for Data Science: Introduction to Data Science with Python
- Harvard University Computer Science Courses: Using Python for Research
- IBM Python Data Science: Visualizing Data with Python
- DeepLearning.AI Data Science and Machine Learning: Deep Learning Specialization
Advanced ⭐⭐⭐⭐⭐
- UC San Diego Data Science: Python for Data Science
- UC San Diego Data Science: Probability and Statistics in Data Science using Python
- Google Data Analysis: Professional Certificate in Advanced Data Analytics
- MIT Statistics and Data Science: Machine Learning with Python - from Linear Models to Deep Learning
- MIT Statistics and Data Science: MicroMasters® Program in Statistics and Data Science
🔎 Find Data Science Programs 👨💻 111,889 already enrolled
Disclaimer: Data Science Parichay is reader supported. When you purchase a course through a link on this site, we may earn a small commission at no additional cost to you. Earned commissions help support this website and its team of writers.
# even values in the array ar print(ar[ar % 2 == 0])
Output:
[2 4 6 8]
We get all the even values in the array ar
.
To understand what’s happening here, let’s look under the hood. Let’s see what we get from the expression ar % 2 == 0
.
ar % 2 == 0
Output:
array([False, True, False, True, False, True, False, True])
We get a Numpy array with boolean values. The values in this array represent whether a value at a particular index satisfies the given condition or not (if the value is even or not).
When we do ar[ar % 2 == 0]
, we are essentially filtering the original array where the condition evaluates to True
.
You can similarly filter a Numpy array for other conditions as well.
Summary – Get all even elements in a Numpy array
In this tutorial, we looked at how to get the even elements of a Numpy array. The following is a short summary of the steps mentioned –
- Create a Numpy array (skip this step if you already have an array to operate on).
- Use boolean indexing to filter the array for only the values that are even,
ar[ar % 2 == 0]
.
You might also be interested in –
Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.