NumPy Startswith Function

Introduction

In this lab, you will learn about the NumPy startswith() function. The startswith() function in the char module of the NumPy library returns a boolean array with values that can be either True or False. This function returns True if the given string starts with the specified prefix value in the function. It returns False if it does not start with the specified prefix.

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

Import Libraries

To use the NumPy library, we first need to import it as shown below.

import numpy as np

Create an input string

For demonstration purposes, we will define an input string.

arr = "The quick brown fox jumps over the lazy dog"

Using the Startswith() Function

Let's use the startswith() function on the input string we created in Step 2.

## Define prefix to be checked as "The"
prefix = 'The'
## Call the startswith() function on a string
print(np.char.startswith(arr, prefix))

Output:

[ True False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False]

Optional Parameters

We can also pass optional parameters to the startswith() function to provide a start and end point for the search.

## Search only between indices 4 and 7
print(np.char.startswith(arr, prefix, start=4, end=7))

Output:

[False False False False]

Check if prefix does not exist

Let's now check the output of the function if the prefix does not exist in the input string.

## Define prefix to be checked as "quick"
prefix = 'quick'
## Call the startswith() function on the input string
print(np.char.startswith(arr, prefix))

Output:

[False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False False]

Summary

In this lab, you learned how to use the startswith() function of the NumPy library to check if a given string starts with a specified prefix. We also went through optional parameters that could be passed to the function. By the end of this lab, you should be able to start using the startswith() function for similar purposes.