text: from linear_model_extension import RegressionStats
  from numpy.testing import assert_equal, assert_allclose
  import numpy as np
  import pandas as pd
  import pytest
  from sklearn.linear_model import LinearRegression
  
  
  
  df = pd.read_csv('data/Boston.csv', index_col = 0)
  
  X = df[['crim']]
  y = df['dis']
  X1 = df[['crim','dis']]
  y1 = df['age']
  
  
  lr_model = LinearRegression().fit(X,y)
  lr_model1 = LinearRegression().fit(X1,y1)
  
  rs = RegressionStats(lr_model, X, y)
  rs1 = RegressionStats(lr_model1, X1, y1)
  
  def test_init():
      with pytest.raises(ValueError, match='X and y different number of samples'):
          assert(RegressionStats(lr_model, X, y[3:]))
          
  def test_colnames():
      assert(rs.colnames == ['Intercept','crim'])
      assert(rs1.colnames == ['Intercept','crim','dis'])
      