blinds statsmodel summary output

blinders.py

class Blinders(object):
    def __init__(self, medusa, peripherals=['Std.Err.', 't', 'P>|t|']):
        '''Helper to only view `peripherals` of `medusa`'''
        # the coefficient we want to blind
        self.medusa = medusa
        # the stats we don't want to blind
        self.peripherals = peripherals
        
    def blind_summary(self, model):
        '''Filters the result of `model.summary2()`'''
        # sm model method summary2() contains the pandas dataframe 
        # that we want to blind
        summary = model.summary2()
        results = summary.tables[1]
        # Find the columns that we want to blind
        blinded_columns = list(set(results.columns) - set(self.peripherals))
        # set the values that we don't want to see to np.nan
        # TODO: is this really the best we can do?
        results.loc[self.medusa, blinded_columns] = np.nan
        return summary
        
    def view_summary(self, model):
        '''Prints a blinded summary of `model`'''
        print(self.blind_summary(model))