TfidfVectorizer does not use the whole set of words in all documents?
Did you check the stop_words and max_features? If you provide values in either of these two, it will exclude some words.
I am trying to build a TFIDF model with TfidfVectorizer. The feature name list namely the number of column of sparse matrix is shorter than the length of word set of documents even though I set min_df as 1. What happened?