code: def _model_fit_to_table(fit):
      
      fit_parameters = pd.DataFrame(
          {'Coefficient': fit.params,
           'Std. Error': fit.bse,
           'T-Score': fit.tvalues})
      fit_parameters.rsquared = fit.rsquared
      fit_parameters.rsquared_adj = fit.rsquared_adj
      return fit_parameters
docs: Produce a pandas DataFrame of model fit results from a statsmodels
      fit result object.
  
      Parameters
      ----------
      fit : statsmodels.regression.linear_model.RegressionResults
  
      Returns
      -------
      fit_parameters : pandas.DataFrame
          Will have columns 'Coefficient', 'Std. Error', and 'T-Score'.
          Index will be model terms.
  
          This frame will also have non-standard attributes
          .rsquared and .rsquared_adj with the same meaning and value
          as on `fit`.