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Stop Words In NLP

This article describes stop words in NLP.

What Are Stop Words?

In NLP, stop words are the common words in a language that usually do not add much meaning and are often removed during preprocessing. Examples of English stop words are a, an, the, in, on, is, was, are, am, be, by, of, with, and, but, or, not, so, too.

Example

Consider the following code: -

from nltk.corpus import stopwords


# Get English stopwords
stop_words = set(stopwords.words('english'))

print(len(stop_words))        # Number of stopwords
print(list(stop_words)[:20])  # First 20 stopwords

Output

How To Remove Stop Words?

Consider the following code: -

from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords


stop_words = set(stopwords.words('english'))

sentence = "This is an example showing off stopwords removal in NLP."
words = word_tokenize(sentence)

filtered = [w for w in words if w.lower() not in stop_words]

print("Original:", words)
print("Without stopwords:", filtered)

Picture showing the collection after removing stop words

Posted By -	Karan Gupta

Posted On -	Friday, August 29, 2025

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