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'Volcom', 'Nautica', 'Quiksilver', 'Diesel', 'Dockers', 'Hurley' ] aggregation_columns = ['brand', 'department', 'category'] # Group purchases by user chronologically df_agg = (df.sort_values('created_at') .groupby(['user_id', 'gender', 'country', 'city', 'age'], as_index=False)[['brand',