|
| Name | Description | Example |
|
| Yearweek | Related yearweek, weeks are starting from Monday to Sunday | 201801 |
| Store | Store number | 1234 |
| Product | Product Identification Number | 1 |
| Product_Adjactive | Associated product with the product according to apriori algorithm. Most frequent product at the same basket with a specific product. | 2 |
| Stock_In_Quantity_Week | Stock increase quantity of the product in related week, ex. stock transfer quantity from distribution center to store. | 50 |
| Return_Quantity_Week | Stock return quantity from customers at a specific week and store | 20 |
| Sales_Quantity_Week | Weekly sales quantity of related product at a specific store | 120 |
| Sales_Amount_Week | Total sales amount of the product at the customer receipt | 2500 |
| Discount_Amount_Week | Discount amount of the product if there is any | 500 |
| Customer_Count_Week | How many customers bought this product at a specific week | 30 |
| Receipt_Count_Week | Distinct receipt count for related product | 20 |
| Sales_Quantity_Time | Hourly sales quantity of related product from 9 am to 22 pm. | 5 |
| Last4weeks_Day | Total sales of each weekday of last 4 weeks. Total sales of Mondays, Tuesdays… etc. | 10 |
| Last8weeks_Day | Total sales of each weekday of last 8 weeks. Total sales of Mondays, Tuesdays… etc. | 10 |
| Max_Stock_Week | Maximum stock quantity of related week. | 12 |
| Min_Stock_Week | Minimum stock quantity of related week | 2 |
| Avg_Stock_Week | Average stock quantity of related week | 5 |
| Sales_Quantity_Adj_Week | Sales quantity of most associated product | 14 |
| Temperature_Weekday | Daily temperature of weekdays. Monday, Tuesday… etc. | 22 |
| Weekly_Avg_Temperature | Average weather temperature of related week. | 23 |
| Weather_Condition_Weekday | Nominal variable; rainy, snowy, sunny, cloudy etc. | Rainy |
| Sales_Quantity_Next_Week | Target variable of our classification problem | 25 |
|
