title: Load and predict new data sklearn
body: <p>I trained a Logistic model, cross-validated and saved it to file using joblib module. Now I want to load this model and predict new data with it. 
  Is this the correct way to do this? Especially the standardization. Should I use scaler.fit() on my new data too? In the tutorials I followed, scaler.fit was only used on the training set, so I'm a bit lost here.</p>
  
  <p>Here is my code:</p>
  
  <pre><code>#Loading the saved model with joblib
  model = joblib.load('model.pkl')
  
  # New data to predict
  pr = pd.read_csv('set_to_predict.csv')
  pred_cols = list(pr.columns.values)[:-1]
  
  # Standardize new data
  scaler = StandardScaler()
  X_pred = scaler.fit(pr[pred_cols]).transform(pr[pred_cols])
  
  pred = pd.Series(model.predict(X_pred))
  print pred
  </code></pre>