title: Naming explanatory variables in regression output
body: <p>Each one of my variables is a list on its own.</p>
  
  <p>I am using a method found on another thread here. </p>
  
  <pre><code>import numpy as np
  import statsmodels.api as sm
  
  y = [1,2,3,4,3,4,5,4,5,5,4,5,4,5,4,5,6,5,4,5,4,3,4]
  
  x = [
       [4,2,3,4,5,4,5,6,7,4,8,9,8,8,6,6,5,5,5,5,5,5,5],
       [4,1,2,3,4,5,6,7,5,8,7,8,7,8,7,8,7,7,7,7,7,6,5],
       [4,1,2,5,6,7,8,9,7,8,7,8,7,7,7,7,7,7,6,6,4,4,4]
       ]
  
  def reg_m(y, x):
      ones = np.ones(len(x[0]))
      X = sm.add_constant(np.column_stack((x[0], ones)))
      for ele in x[1:]:
          X = sm.add_constant(np.column_stack((ele, X)))
      results = sm.OLS(y, X).fit()
      return results
  </code></pre>
  
  <p>My only problem being, that in my regression output, the explanatory variables are labelled x1, x2, x3 etc. Was wondering if it was possible to change these to more meaningful names?</p>
  
  <p>Thanks</p>