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# You might need to parse the response (often JSON or XML) into a DataFrame df = pd.read_json(response.content)

# Process and filter the data to get your list common_words = df['word'].head(20000).tolist() # Further processing, saving to a PDF, etc. Keep in mind that actual implementation would depend on the data's format and accessibility.

If you have specific requirements (like only general vocabulary, no proper nouns, etc.), you'll need to filter your list accordingly.

# Assuming you have a URL or API to COCA data url = "some_url_to_coca_data" response = requests.get(url)

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# You might need to parse the response (often JSON or XML) into a DataFrame df = pd.read_json(response.content)

# Process and filter the data to get your list common_words = df['word'].head(20000).tolist() # Further processing, saving to a PDF, etc. Keep in mind that actual implementation would depend on the data's format and accessibility. 20000 most common english words pdf new

If you have specific requirements (like only general vocabulary, no proper nouns, etc.), you'll need to filter your list accordingly. # You might need to parse the response

# Assuming you have a URL or API to COCA data url = "some_url_to_coca_data" response = requests.get(url) saving to a PDF