In this tutorial, we will look at how to check if a value in a Numpy array is finite or not with the help of some examples.
How to test for finiteness in a Numpy array?
You can use the numpy.isfinite()
function to check (element-wise) if values in a Numpy array are finite or not. The following is the syntax –
# test for finiteness - pass scaler value or numpy array np.isfinite(a)
It returns a boolean value (True
if the value is finite otherwise False
) if you pass a scaler value and a 1-D boolean array if you pass an array.
Examples
Let’s now look at some examples of using the above function to test for finiteness.
Example 1 – Check if a number is finite or not using numpy.isfinite()
First, let’s pass scaler values to the numpy.isfinite()
function.
Let’s create three variables – one containing a finite value and the others set to positive and negative infinity respectively and then apply the numpy.isfinite()
function on each of these values.
import numpy as np # create three variables with scaler values a = 21 b = np.inf c = -np.inf # check if finite print(np.isfinite(a)) print(np.isfinite(b)) print(np.isfinite(c))
Output:
True False False
We get True
as the output for the scaler value 21
and False
as the output for both the positive and the negative infinity values.
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.
Example 2 – Element-wise check for finiteness in a Numpy array using numpy.isfinite()
If you apply the numpy.isfinite()
function on an array, it will return a boolean array containing with True
for values that are finite and False
for infinity values.
Let’s create a 1-D array and apply the numpy.isfinite()
function to it.
# create a numpy array ar = np.array([1, 2, np.inf, 4, 5, -np.inf, np.inf]) # element-wise check for finite value in ar np.isfinite(ar)
Output:
array([ True, True, False, True, True, False, False])
We get a boolean array as an output. You can see that in the boolean array we get True
for only the values that test as finite in the original array.
Summary
In this tutorial, we looked at how we can use the numpy.isfinite()
function to check if an element is finite or not in a Numpy array. Keep in mind that if you pass a scaler value, it returns a boolean value and if you pass a 1-D array it returns a boolean array.
You might also be interested in –
- Numpy – Check If Element is an Infinity or Not
- Check If Two Numpy Arrays are Equal
- Numpy – Count Values Between a Given Range
Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.