Stopword removal with NLTK

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There is an in-built stopword list in NLTK made up of 2,400 stopwords for 11 languages (Porter et al), see http://nltk.org/book/ch02.html

>>> from nltk import word_tokenize
>>> from nltk.corpus import stopwords
>>> stop = set(stopwords.words('english'))
>>> sentence = "this is a foo bar sentence"
>>> print([i for i in sentence.lower().split() if i not in stop])
['foo', 'bar', 'sentence']
>>> [i for i in word_tokenize(sentence.lower()) if i not in stop] 
['foo', 'bar', 'sentence']

I recommend looking at using tf-idf to remove stopwords, see Effects of Stemming on the term frequency?

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