Historical customer data for a fictional outdoor equipment store used in Watson Studio tutorials train the machine learning models. This set of Go customer data is derived from the Order Methods, Products, Retailers and Sales dataset of the Go Sales dataset. The sample data is structured in rows and columns, and saved in a .csv file.
Feature datasets and columns
- Go product: Information on the ID and quantity of sale items
Retailer codeProduct numberDateQuantity: Number of items
- Go Daily Sales:
Retailer codeProduct numberOrder Method Code: Sequential numerical code for order method typeDateQuantity: Number of itemsUnit Price: Regular price of itemUnit Sale Price: Sales price of item
- Go Methods:
Order Method Code: Sequential numerical code for order method typeOrder Method Type: "Fax", "Telephone", "Mail", "E-mail", "Web", "Sales visit", "Special", "Other"
- Go Products:
Product numberProduct line: "Camping Equipment", "Mountaineering Equipment", "Personal Accessories", "Outdoor Protection", "Golf Equipment"Product type: "Cooking Gear", "Tents", "Sleeping Bags" and moreProduct: "TrailChef Water Bag", "TrailChef Canteen", "TrailChef Kitchen Kit" and moreProduct brand: "TrailChef", "Star", "Hibernator" and moreProduct color: "Clear", "Brown", "Silver" and moreUnit cost: Cost to supply unit in shopUnit price: Regular price of item
- Go Retailers:
Retailer codeRetailer nameType: Type of retailer storeCountry: Retailer store's country of origin
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