title: Python, ValueError, BroadCast Error with SKLearn Preproccesing
body: <p>I am trying to run SKLearn Preprocessing standard scaler function and I receive the following error:</p>
  
  <pre><code>from sklearn import preprocessing as pre
  scaler = pre.StandardScaler().fit(t_train)
  t_train_scale = scaler.transform(t_train)
  t_test_scale = scaler.transform(t_test)
  
  ---------------------------------------------------------------------------
  ValueError                                Traceback (most recent call last)
  &lt;ipython-input-149-c0133b7e399b&gt; in &lt;module&gt;()
        4 scaler = pre.StandardScaler().fit(t_train)
        5 t_train_scale = scaler.transform(t_train)
  
  ----&gt; 6 t_test_scale = scaler.transform(t_test)
  
  C:\Users\****\Anaconda\lib\site-packages\sklearn\preprocessing\data.pyc in transform(self, X, y, copy)
      356         else:
      357             if self.with_mean:
  --&gt; 358                 X -= self.mean_
      359             if self.with_std:
      360                 X /= self.std_
  
  ValueError: operands could not be broadcast together with shapes (40000,59) (119,) (40000,59) 
  </code></pre>
  
  <p>I understand the shapes do not match. The train and test data set are different lengths so how would I transform the data?</p>