text_plain_output_1.png
from nltk.stem.lancaster import LancasterStemmer

from nltk.tokenize import word_tokenize, sent_tokenize

text2.concordance('monstrous')

text2.similar('monstrous')

text2.common_contexts(['monstrous', 'very'])

text2 = 'Mary closed on closing night when she was in the mood to close.'

st = LancasterStemmer()

stemmedWords = [st.stem(word) for word in word_tokenize(text2)]

print(stemmedWords)