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- from sklearn.feature_extraction.text import TfidfVectorizer
- tfidf_vectorizer = TfidfVectorizer(norm=None)
- list_contents =[]
- for index, row in df.iterrows():
- list_contents.append(' '.join(row.Tokens))
- # list_contents = df.Content.values
- tfidf_matrix = tfidf_vectorizer.fit_transform(list_contents)
- df_tfidf = pd.DataFrame(tfidf_matrix.toarray(),columns= [tfidf_vectorizer.get_feature_names()])
- df_tfidf.head(10)
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