J Pollyfan Nicole Pusycat Set Docx Repack -

# Extract text from the document text = [] for para in doc.paragraphs: text.append(para.text) text = '\n'.join(text)

# Calculate word frequency word_freq = nltk.FreqDist(tokens) J Pollyfan Nicole PusyCat Set docx

# Tokenize the text tokens = word_tokenize(text) # Extract text from the document text = [] for para in doc

# Remove stopwords and punctuation stop_words = set(stopwords.words('english')) tokens = [t for t in tokens if t.isalpha() and t not in stop_words] removes stopwords and punctuation

import docx import nltk from nltk.tokenize import word_tokenize from nltk.corpus import stopwords

# Print the top 10 most common words print(word_freq.most_common(10)) This code extracts the text from the docx file, tokenizes it, removes stopwords and punctuation, and calculates the word frequency. You can build upon this code to generate additional features.

Here are some features that can be extracted or generated: