NumPy Trunc Function

Introduction

In this lab, we will learn about the NumPy trunc() function in the Python language. We will understand its syntax, parameters, and how to use this function to return the truncated value of input array elements. We will also see some examples to have a better understanding.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

Importing NumPy Library

First, we need to import the NumPy library using the import statement before using its functions.

import numpy as np

Basic Example

In the second step, we will learn to use numpy.trunc() in a basic example.

x = [1.2,-0.344,5.89]
y = np.trunc(x)
print(y)

Output:

array([ 1., -0.,  5.])

Trunc Function with an Input Array

In this step, we will learn to use numpy.trunc() function with an input array.

inp = [123.22,23.4,0.89]
print("The Input array is :")
print(inp)
x = np.trunc(inp)
print("The Output array is :")
print(x)

Output:

The Input array is :
[123.22, 23.4, 0.89]
The Output array is :
[123.  23.   0.]

Summary

In this tutorial, we learned about numpy.trunc() function in the NumPy library of Python language to return the truncated value of input array elements. We studied its syntax, parameters as well as the value returned by this function. We also saw some code examples demonstrating its usage and output.