### Statmodels output different from sklearn regression

I am trying to get something magic from the boston dataset on sklearn. Wihtout making any change I did a regression with sklearn and another with statsmodels to easily get the p-value of my each of the variables used. However, my reults are completely different results. Here it is: boston_houses=load_boston() boston=pd.DataFrame(data=boston_houses.data, columns=boston_houses.feature_names) boston[‘MEDV’]=boston_houses.target boston.head() X,y=boston.drop(columns=’MEDV’),boston[‘MEDV’]…

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