def clean(text: str) -> list:
    'A simple function to cleanup text data'
    wnl = nltk.stem.WordNetLemmatizer()
    stopwords = nltk.corpus.stopwords.words('english')
    text = text.encode('ascii', 'ignore').decode('utf-8', 'ignore').lower()
    words = re.sub('[^\\w\\s]', '', text).split()
    return [wnl.lemmatize(word) for word in words if (word not in stopwords)]
A simple function to cleanup text data
def clean(text: str) -> list:
    
    wnl = nltk.stem.WordNetLemmatizer()
    stopwords = nltk.corpus.stopwords.words('english')
    text = text.encode('ascii', 'ignore').decode('utf-8', 'ignore').lower()
    words = re.sub('[^\\w\\s]', , text).split()
    return [wnl.lemmatize(word) for word in words if (word not in stopwords)]