Dds Ss Mila 025 9yrs Red String Thong 212pics Best [FAST]

# Convert to a DataFrame for easier viewing feature_df = pd.DataFrame(X.toarray(), columns=vectorizer.get_feature_names_out()) Disebuah Kolam Renang Best: Juq773 Drama Ntr Terlarang

# Simple preprocessing df['description'] = df['description'].apply(lambda x: re.sub(r'\d+', '', x)) # Remove numbers Anna Ralphs Solo 📥

# Sample data data = { "description": ["dds ss mila 025 9yrs red string thong 212pics best"] }

# Initialize a TF-IDF vectorizer vectorizer = TfidfVectorizer()

print(feature_df) The preprocessing steps and features you choose should be guided by the requirements of your project or analysis. If you're working with sensitive content, ensure you're complying with platform and legal guidelines.

# Fit and transform the data X = vectorizer.fit_transform(df['description'])

import pandas as pd from sklearn.feature_extraction.text import TfidfVectorizer import re