CountVectorizer does not print vocabulary

Question

I have installed python 2.7, numpy 1.9.0, scipy 0.15.1 and scikit-learn 0.15.2. Now when I do the following in python:

train_set = (\"The sky is blue.\", \"The          


        

Answer 1

You are missing an underscore, try this way:

from sklearn.feature_extraction.text import CountVectorizer
train_set = ("The sky is blue.", "The sun is bright.")
test_set = ("The sun in the sky is bright.", 
    "We can see the shining sun, the bright sun.")

vectorizer = CountVectorizer(stop_words='english')
document_term_matrix = vectorizer.fit_transform(train_set)
print vectorizer.vocabulary_
# {u'blue': 0, u'sun': 3, u'bright': 1, u'sky': 2}

If you use the ipython shell, you can use tab completion, and you can find easier the methods and attributes of objects.

Answer 2

Try using the vectorizer.get_feature_names() method. It gives the column names in the order it appears in the document_term_matrix.

from sklearn.feature_extraction.text import CountVectorizer
train_set = ("The sky is blue.", "The sun is bright.")
test_set = ("The sun in the sky is bright.", 
    "We can see the shining sun, the bright sun.")

vectorizer = CountVectorizer(stop_words='english')
document_term_matrix = vectorizer.fit_transform(train_set)
vectorizer.get_feature_names()
#> ['blue', 'bright', 'sky', 'sun']