final_aggregation.py

# Aggregate the data a bit
orders_with_meals['Meal Price / Order Value'] = orders_with_meals['Meal Price']/orders_with_meals['Order Value']
orders_with_meals['Meal Price / Order Value'] = pd.qcut(
    orders_with_meals['Meal Price / Order Value']*-1,
    5,
    labels = ['Least Expensive','Less Expensive','Proportional','More Expensive','Most Expensive'][::-1]
)

orders_with_meals['Timing of Meal'] = pd.qcut(
    orders_with_meals['Days of meal before order'],
    3,
    labels = ['After Order','Around Order','Before Order']
)


data = orders_with_meals[orders_with_meals['Type of Meal'] != 'no meal'].groupby(
    ['Timing of Meal','Number Participants','Type of Meal','Meal Price / Order Value']
).agg({'Converted': np.mean}).unstack().fillna(0).stack().reset_index()