title: Admitted data type in RFE to keep features in a logistic regression
body: <p>I'm trying to build a logistic regression in python with a dataset that contains continuous features and some binary features.</p>
  
  <p>In order to choose the features that I will include in the model I am using RFE. So basically I have this code</p>
  
  <pre><code>y=HRData['left']
  collist = HRData.columns.tolist()
  collist.remove('left')
  X=HRData[collist]
  model = LogisticRegression()
  rfe = RFE(model, 10)
  fit = rfe.fit(HRData[X], HRData[y])
  </code></pre>
  
  <p>where y contains 1's and 0's and X has either int or float data.</p>
  
  <h2>When I try to fit the model with RFE I keep getting this:</h2>
  
  <pre><code>/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in 
  _getitem_frame(self, key)
     2033     def _getitem_frame(self, key):
     2034         if key.values.size and not is_bool_dtype(key.values):
  -&gt; 2035             raise ValueError('Must pass DataFrame with boolean values only')
     2036         return self.where(key)
     2037 
  </code></pre>
  
  <h2>       ValueError: Must pass DataFrame with boolean values only</h2>
  
  <p>So I am not sure if this function only admits data frames with boolean values since I've seen examples with continuous variables. </p>
  
  <p>Thanks in advance for your help!</p>