Python 2.7 如何使用tfidf-python转换数据

我得到的错误如下：

from sklearn.feature_extraction.text import TfidfVectorizer
transformer = TfidfVectorizer(stop_words="english")
word_data_trans = transformer.fit_transform(word_data)

---

我不知道我现在没有做什么

这是同一个问题吗？你能发布一个

word\u数据样本吗？以及完整的错误消息（如果可能）。
79 from sklearn.feature_extraction.text import TfidfVectorizer
     80 transformer = TfidfVectorizer(stop_words="english")
---> 81 word_data_trans = transformer.fit_transform(word_data)
     82 word_list = transformer.get_feature_names()
     83 print "Length of word_list: ", len(word_list)

C:\ProgramData\Anaconda3\envs\ipykernel_py2\lib\site-packages\sklearn\feature_extraction\text.pyc in fit_transform(self, raw_documents, y)
   1379             Tf-idf-weighted document-term matrix.
   1380         """
-> 1381         X = super(TfidfVectorizer, self).fit_transform(raw_documents)
   1382         self._tfidf.fit(X)
   1383         # X is already a transformed view of raw_documents so