Challenge: Stemming the Tokens
Compito
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Your task is the following:
- Import Porter Stemmer.
- Convert
textto lowercase. - Tokenize the
textstring. - Load English stop words.
- Filter out the stop words using list comprehension.
- Create a stemmer object.
- Stem the tokens using list comprehension.
Soluzione
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from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
# Import Porter Stemmer
from nltk.stem import PorterStemmer
import nltk
nltk.download('punkt_tab')
nltk.download('stopwords')
text = "Despite the pouring rain, the overwhelming sense of joy and accomplishment made the day unforgettable!"
# Convert the text to lowercase
text = text.lower()
# Tokenization
tokens = word_tokenize(text)
# Load English stop words
stop_words = set(stopwords.words('english'))
# Remove stop words (use list comprehension)
filtered_tokens = [token for token in tokens if token.lower() not in stop_words]
# Create a stemmer object
stemmer = PorterStemmer()
# Stemming (use list comprehension)
stemmed_tokens = [stemmer.stem(token) for token in filtered_tokens]
print("Stemmed tokens:", stemmed_tokens)
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Sezione 2. Capitolo 2
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from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
# Import Porter Stemmer
from ___ import ____
import nltk
nltk.download('punkt_tab')
nltk.download('stopwords')
text = "Despite the pouring rain, the overwhelming sense of joy and accomplishment made the day unforgettable!"
# Convert the text to lowercase
text = ___
# Tokenization
tokens = ___
# Load English stop words
stop_words = set(___)
# Remove stop words (use list comprehension)
filtered_tokens = [token for ___ in tokens if ___]
# Create a stemmer object
stemmer = ___
# Stemming (use list comprehension)
stemmed_tokens = [___ for token in ___]
print("Stemmed tokens:", stemmed_tokens)
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