title: sklearn Linear Regression coefficients have single value output
body: <p>I am using dataset to see the relationship between salary and college GPA. I am using sklearn linear regression model. I think the coefficients should be intercept and the coff. value of corresponding feature. But the model is giving a single value. </p>
  
  <pre><code>from sklearn.cross_validation import train_test_split
  from sklearn.linear_model import LinearRegression
  
  # Use only one feature : CollegeGPA
  labour_data_gpa = labour_data[['collegeGPA']]
  
  # salary as a dependent variable
  labour_data_salary = labour_data[['Salary']]
  
  # Split the data into training/testing sets
  gpa_train, gpa_test, salary_train, salary_test = train_test_split(labour_data_gpa, labour_data_salary)
  
  # Create linear regression object
   regression = LinearRegression()
  
  # Train the model using the training sets (first parameter is x )
   regression.fit(gpa_train, salary_train)
  
  #coefficients 
  regression.coef_
  
  The output is : Out[12]: array([[ 3235.66359637]])
  </code></pre>