title: Predict for each sample, check the value in pandas dataframe and append to a new dataframe
body: <p>I am a newbie in machine learning using python and pandas dataframe.
  I am training my model and making predictions on the x_test(dataframe).
  I want to make the predictions for each row(sample) in the x_test and want to append that row to a new dataframe(new_train) if the prediction value is less than some value(0.4). I have provided the body of my idea. Could you please help me out?</p>
  
  <pre><code> c = XGBRegressor()  
   dt = c.fit(x_train, y_train)
  
   new_train = pd.DataFrame()  
  
   for rows in x_test:  
       y_pred = c.predict(x_test[rows])  
       if y_pred &lt; 0.4:
             new_train.append(x_test[rows])
  </code></pre>