Tutorial: Removing Stop Words Using NLTK

Stop words are common words like “the,” “is,” “in,” which are generally filtered out while processing text data. They are considered noise in the text and are often eliminated to retain only the most important words that are relevant to the process you are performing. In this tutorial, we’ll cover removing stop words using NLTK in Python.

Table of Contents

• Prerequisites
• Installing NLTK
• Importing Required Libraries
• Fetching Stop Words
• Removing Stop Words
• FAQs

Prerequisites

• Python installed on your system
• Basic understanding of Python programming
• Familiarity with Natural Language Processing (NLP)

Installing NLTK

If you haven’t installed NLTK yet, you can install it using pip:Installing NLTK on Windows, Mac and Linux

Importing Required Libraries

First, we need to import the libraries that we’ll be using.

import nltk
from nltk.corpus import stopwords

Fetching Stop Words

Before you can remove stop words, you need to download the stop words package from NLTK’s data repository.

nltk.download('stopwords')

Removing Stop Words

Once the package is downloaded, you can proceed with stop word removal.

# Sample text
text = "This is a sample sentence that we will use to remove stop words."

# Tokenize the text
word_tokens = nltk.word_tokenize(text)

# Fetch the stop words
stop_words = set(stopwords.words('english'))

# Remove stop words
filtered_words = [word for word in word_tokens if word.lower() not in stop_words]

# Output
print("Original Sentence:", text)
print("Filtered Sentence:", ' '.join(filtered_words))

FAQs

Q. What are stop words?

A. Stop words are common words that are generally ignored in text data processing because they occur frequently and don’t carry significant meaning.

Q. Can I add my own custom stop words?

A. Yes, you can extend the list of stop words by simply adding to the stop_words set that we defined. For example,

 stop_words.add("new_word")

Q. Do all languages have stop words in NLTK?

A. NLTK includes stop words lists for many languages, though not all. You can check the available languages by running

 stopwords.fileids()

Q. Is it always necessary to remove stop words?

A. No, the necessity to remove stop words depends on the application. In some cases, like sentiment analysis, stop words can carry sentiment and might be useful.

Q. What if my text is not in English?

A. NLTK supports stop word removal for various languages. You can specify the language while fetching the stop words. For example, for Spanish, you would use stopwords.words('spanish').

That’s the end of our tutorial on removing stop words using NLTK. With this, you should be equipped to clean text data effectively for your NLP projects.