Dividing text data into chunks

Text data usually needs to be divided into pieces for further analysis. This process is known as chunking. This is used frequently in text analysis. The conditions that are used to divide the text into chunks can vary based on the problem at hand. This is not the same as tokenization, where text is also divided into pieces. During chunking, we do not adhere to any constraints, except for the fact that the output chunks need to be meaningful.

When we deal with large text documents, it becomes important to divide the text into chunks to extract meaningful information. In this section, we will see how to divide input text into several pieces.

Create a new Python file and import the following packages:

import numpy as np
from nltk.corpus import brown

Define a function to divide the input text into chunks. The first parameter is the text, and the second parameter is the number of words in each chunk:

# Split the input text into chunks...