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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _model_fit_to_table(fit):
 """ 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`. """

    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