get absolute value of each array element in numpy array

Numpy – Get Absolute Value of Each Element

The Numpy library in Python comes with a number of built-in functions to perform common mathematical operations on arrays. In this tutorial, we will look at one such function that helps us get the elementwise absolute value of a Numpy array with the help of some examples.

How to get the absolute value in Numpy?

get absolute value of each array element in numpy array

You can use the numpy.absolute() function to get the absolute value of each element in a Numpy array. Pass the array as an argument.

The following is the syntax –

numpy.absolute(ar)

It returns an array containing the absolute value of each element in the passed array.

Let’s now look at a step-by-step example of using the numpy.absolute() function.

Step 1 – Create a Numpy array

First, we will create a Numpy array that we will use throughout this tutorial.

import numpy as np

# create numpy array
ar = np.array([1, -3, 4, 0, 5, -2, -7])
# display the array
print(ar)

Output:

[ 1 -3  4  0  5 -2 -7]

Here, we used the numpy.array() function to create a Numpy array containing some numbers. You can see that this array contains both positive and negative numbers (along with a 0).

📚 Data Science Programs By Skill Level

Introductory

Intermediate ⭐⭐⭐

Advanced ⭐⭐⭐⭐⭐

🔎 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.

Step 2 – Get absolute value using numpy.absolute()

To get the absolute value of each element in a Numpy array, pass the array as an argument to the numpy.absolute() function.

Let’s get the absolute value for the array created above.

# get absolute value
np.absolute(ar)

Output:

array([1, 3, 4, 0, 5, 2, 7])

We get a Numpy array with the absolute value of each element in the array ar.

You can also use numpy.abs() as a shorthand for the numpy.absolute() function.

# get absolute value
np.abs(ar)

Output:

array([1, 3, 4, 0, 5, 2, 7])

We get the same result as above.

The numpy.absolute() function works similarly on higher-dimensional arrays. For example, let’s apply this function to a 2D array of some numbers.

# create 2D numpy array
ar = np.array([[1, -3, 4],
               [0, 5, -2],
               [-6, 8, -7]])
# get absolute value
np.abs(ar)

Output:

array([[1, 3, 4],
       [0, 5, 2],
       [6, 8, 7]])

You can see that we get the absolute value of each element in the 2D array.

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

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.


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.

Scroll to Top