I was reading about TfidfVectorizer [implementation](http://stanford.edu/~rjweiss/public_html/IRiSS2013/text2/notebooks/tfidf.html) of scikit-learn, i don´t understand what´s the output of the method, for example:

```
new_docs = ['He watches basketball and baseball', 'Julie likes to play basketball', 'Jane loves to play baseball']
new_term_freq_matrix = tfidf_vectorizer.transform(new_docs)
print tfidf_vectorizer.vocabulary_
print new_term_freq_matrix.todense()

```

output:

```
{u'me': 8, u'basketball': 1, u'julie': 4, u'baseball': 0, u'likes': 5, u'loves': 7, u'jane': 3, u'linda': 6, u'more': 9, u'than': 10, u'he': 2}
[[ 0.57735027  0.57735027  0.57735027  0.          0.          0.          0.
   0.          0.          0.          0.        ]
 [ 0.          0.68091856  0.          0.          0.51785612  0.51785612
   0.          0.          0.          0.          0.        ]
 [ 0.62276601  0.          0.          0.62276601  0.          0.          0.
   0.4736296   0.          0.          0.        ]]

```

What is?(e.g.: u'me': 8 ):

```
{u'me': 8, u'basketball': 1, u'julie': 4, u'baseball': 0, u'likes': 5, u'loves': 7, u'jane': 3, u'linda': 6, u'more': 9, u'than': 10, u'he': 2}

```

is this a matrix or just a vector?, i can´t understand what´s telling me the output:

```
[[ 0.57735027  0.57735027  0.57735027  0.          0.          0.          0.
   0.          0.          0.          0.        ]
 [ 0.          0.68091856  0.          0.          0.51785612  0.51785612
   0.          0.          0.          0.          0.        ]
 [ 0.62276601  0.          0.          0.62276601  0.          0.          0.
   0.4736296   0.          0.          0.        ]]

```

Could anybody explain me in more detail these outputs?

Thanks!