title: Issue with OneHotEncoder for categorical features
body: <p>I want to encode 3 categorical features out of 10 features in my datasets. I use <code>preprocessing</code> from <a href="http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html" rel="noreferrer">sklearn.preprocessing</a> to do so as the following:</p>
  
  <pre><code>from sklearn import preprocessing
  cat_features = ['color', 'director_name', 'actor_2_name']
  enc = preprocessing.OneHotEncoder(categorical_features=cat_features)
  enc.fit(dataset.values)
  </code></pre>
  
  <p>However, I couldn't proceed as I am getting this error:</p>
  
  <pre><code>    array = np.array(array, dtype=dtype, order=order, copy=copy)
  ValueError: could not convert string to float: PG
  </code></pre>
  
  <p>I am surprised why it is complaining about the string as it is supposed to convert it!! Am I missing something here?</p>