Stop Words In NLP

a, an, the, in, on, is, was, are, am, be, by, of, with, and, but, or, not, so, too

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

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)

Query/Feedback