### utlity function for pre-processing the text import spacy # load english language model and create nlp object from it nlp = spacy.load("en_core_web_sm") def preprocess(text): # remove stop words and lemmatize the text doc = nlp(text) filtered_tokens = [] for token in doc: if token.is_stop or token.is_punct: continue filtered_tokens.append(token.lemma_) return " ".join(filtered_tokens) df['preprocessed_txt'] = df['Text'].apply(preprocess)
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