bike_sales: Fictional sales data for bike shops purchasing Cannondale...
In sweep: Tidy Tools for Forecasting
bike_sales R Documentation
Fictional sales data for bike shops purchasing Cannondale bikes
Description
A dataset containing the fictional bicycle orders spanning 2011 through 2015.
Hypothetically, the bike_sales data are similar to sales data mainatained
in a business' sales data base. The unit price and model names come from
data provided by model for the bicycle manufacturer, Cannondale (2016).
The customers (bicycle shops) including name, location, etc and
the orders including quantity purchased and order dates are fictional.
The data is intended for implementing business analytics techniques
(e.g. forecast, clustering, etc) to identify underlying trends.
Usage
bike_sales
Format
A data frame with 15644 rows and 17 variables:
- order.date
Date the order was placed
- order.id
A unique order identification number
- order.line
The sequential identification number for products on and order
- quantity
Number of units purchased
- price
The unit price of the bicycle
- price.ext
The extended price = price x quantity
- customer.id
A unique customer identification number
- bikeshop.name
The customer name
- bikeshop.city
The city that the bike shop is located
- bikeshop.state
The state that the bike shop is located
- latitude
The geograhpic latitude of the customer location
- longitude
The geograhpic longitude of the customer location
- product.id
A unique product identification number
- model
The model name of the bicycle
- category.primary
The main bicycle category, either "Mountain" or "Road"
- category.secondary
One of nine more specific bicycle categories
- frame
The bicycle frame material, either "Carbon" or "Aluminum"
Source
The 2016 bicycle model names and prices originated from https://www.cannondale.com/en-us
sweep documentation built on July 9, 2023, 7:10 p.m.
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| bike_sales | R Documentation |
Fictional sales data for bike shops purchasing Cannondale bikes
Description
A dataset containing the fictional bicycle orders spanning 2011 through 2015.
Hypothetically, the bike_sales data are similar to sales data mainatained
in a business' sales data base. The unit price and model names come from
data provided by model for the bicycle manufacturer, Cannondale (2016).
The customers (bicycle shops) including name, location, etc and
the orders including quantity purchased and order dates are fictional.
The data is intended for implementing business analytics techniques
(e.g. forecast, clustering, etc) to identify underlying trends.
Usage
bike_sales
Format
A data frame with 15644 rows and 17 variables:
- order.date
Date the order was placed
- order.id
A unique order identification number
- order.line
The sequential identification number for products on and order
- quantity
Number of units purchased
- price
The unit price of the bicycle
- price.ext
The extended price = price x quantity
- customer.id
A unique customer identification number
- bikeshop.name
The customer name
- bikeshop.city
The city that the bike shop is located
- bikeshop.state
The state that the bike shop is located
- latitude
The geograhpic latitude of the customer location
- longitude
The geograhpic longitude of the customer location
- product.id
A unique product identification number
- model
The model name of the bicycle
- category.primary
The main bicycle category, either "Mountain" or "Road"
- category.secondary
One of nine more specific bicycle categories
- frame
The bicycle frame material, either "Carbon" or "Aluminum"
Source
The 2016 bicycle model names and prices originated from https://www.cannondale.com/en-us
R Package Documentation
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