Bag of words question

[zivoni]

from sklearn.feature_extraction.text import CountVectorizer

sentences = ['dont iterate over rows of dataframe',
             'try to use dataframe indexing']

vec = CountVectorizer()
vectors = vec.fit_transform(sentences).toarray()

print(sorted(((v, k) for k,v in vec.vocabulary_.items())))
print(vectors[0])
print(vectors[1])

Output:
[(0, 'dataframe'), (1, 'dont'), (2, 'indexing'), (3, 'iterate'), (4, 'of'), (5, 'over'), (6, 'rows'), (7, 'to'), (8, 'try'), (9, 'use')]
[1 1 0 1 1 1 1 0 0 0]
[1 0 1 0 0 0 0 1 1 1]