title: PYTHON: line of best fit for multiple y values per x value
body: <p>I am plotting a 1d array (x-axis) against a 2d array (y-axis)in matplotlib so there are multiple y values for each x value. I want to plot a straigt line of best fit (linear regression), not just a line joining the points. How can I do this???</p>
  
  <p>All the otehr examples seem to only have one y value per x value. When I use 'from sklearn.linear_model import LinearRegression' I get as many best fit lines as there are y values per x value.</p>
  
  <p>EDIT: here is the code I have tried:</p>
  
  <pre><code>model = LinearRegression()
  x_axis2 = np.arange(0,len(av_rsq3))
  x_axis2 = x_axis2.reshape(-1,1)
  model.fit(x_axis2, av_rsq3)
  pt.figure()
  pt.plot(x_axis2,av_rsq3, 'rx')
  pt.plot(x_axis2, model.predict(x_axis2))
  </code></pre>
  
  <p>note: x_axis2 is a 1d array and av_rsq3 is a 2d array. </p>