tips = sns.load_dataset('tips')

def plot_good_tip(day, total_bill, **kws):
    expected_tip = total_bill.groupby(day).mean().apply(lambda x: x * 0.2
        ).reset_index(name='tip')
sns.pointplot(expected_tip.day, expected_tip.tip, linestyles=['--'],
    markers=['D'])
g = sns.FacetGrid(tips, col='sex', size=5)
g.map(sns.pointplot, 'day', 'tip')
g.map(plot_good_tip, 'day', 'total_bill')
g.set_axis_labels('day', 'tip')
Showing data and model predictions in one plot using Seaborn and Statsmodels