title: How to predict y value with test data set?
body: <p>I have successfully built logistic regression model using train dataset below.</p>
  
  <pre><code>X = train.drop('y', axis=1)
  y = train['y']
  
  X_train, X_test, y_train, y_test = train_test_split(X, y, 
                                                      test_size=0.5)
  
  scaler = StandardScaler()  
  scaler.fit(X_train)
  
  X_train = scaler.transform(X_train)
  X_test = scaler.transform(X_test)
  
  logreg1 = LogisticRegression()
  logreg1.fit(X_train, y_train)
  
  score = logreg1.score(X_test, y_test)
  cvs = cross_val_score(logreg1, X_test, y_test, cv=5).mean()
  </code></pre>
  
  <p>My problem is I want to bring in the test dataset to predict the unknown y value. In the test data theres no y column. How can I predict the y value using the seperate test dataset?? </p>