Causes error. Seems to be related to type.

sklearn-pandas bug?

import pandas as pd
from sklearn_pandas import DataFrameMapper
from sklearn.feature_extraction.text import CountVectorizer

df = pd.DataFrame({"content":["tim hopper", "this data tim"]})
mapper = DataFrameMapper([("content", CountVectorizer())])
mapper.fit_transform(df)

The error I get from the code below

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-7-01896d0e98b9> in <module>()
      5 df = pd.DataFrame({"content":["tim hopper", "this data tim"]})
      6 mapper = DataFrameMapper([("content", CountVectorizer())])
----> 7 mapper.fit_transform(df)

C:\Anaconda\lib\site-packages\sklearn\base.pyc in fit_transform(self, X, y, **fit_params)
    406         if y is None:
    407             # fit method of arity 1 (unsupervised transformation)
--> 408             return self.fit(X, **fit_params).transform(X)
    409         else:
    410             # fit method of arity 2 (supervised transformation)

C:\Anaconda\lib\site-packages\sklearn_pandas\__init__.pyc in fit(self, X, y)
    100         for columns, transformer in self.features:
    101             if transformer is not None:
--> 102                 transformer.fit(self._get_col_subset(X, columns))
    103         return self
    104 

C:\Anaconda\lib\site-packages\sklearn\feature_extraction\text.pyc in fit(self, raw_documents, y)
    754         self
    755         """
--> 756         self.fit_transform(raw_documents)
    757         return self
    758 

C:\Anaconda\lib\site-packages\sklearn\feature_extraction\text.pyc in fit_transform(self, raw_documents, y)
    778         max_features = self.max_features
    779 
--> 780         vocabulary, X = self._count_vocab(raw_documents, self.fixed_vocabulary)
    781         X = X.tocsc()
    782 

C:\Anaconda\lib\site-packages\sklearn\feature_extraction\text.pyc in _count_vocab(self, raw_documents, fixed_vocab)
    713         indptr.append(0)
    714         for doc in raw_documents:
--> 715             for feature in analyze(doc):
    716                 try:
    717                     j_indices.append(vocabulary[feature])

C:\Anaconda\lib\site-packages\sklearn\feature_extraction\text.pyc in <lambda>(doc)
    227 
    228             return lambda doc: self._word_ngrams(
--> 229                 tokenize(preprocess(self.decode(doc))), stop_words)
    230 
    231         else:

C:\Anaconda\lib\site-packages\sklearn\feature_extraction\text.pyc in <lambda>(x)
    193 
    194         if self.lowercase:
--> 195             return lambda x: strip_accents(x.lower())
    196         else:
    197             return strip_accents

AttributeError: 'numpy.ndarray' object has no attribute 'lower'