countvectorizer sklearn code example

Example 1: countvectorizer with list of list

corpus = [["this is spam, 'SPAM'"],["this is ham, 'HAM'"],["this is nothing, 'NOTHING'"]]

from sklearn.feature_extraction.text import CountVectorizer
bag_of_words = CountVectorizer(tokenizer=lambda doc: doc, lowercase=False).fit_transform(splited_labels_from_corpus)

Example 2: CountVectorizer

vectorizer2.get_feature_names()