SOLD26 {regclass} | R Documentation |
Predicting future sales
Description
Predicting future sales based on sales data in first quarter after release
Usage
data("SOLD26")
Format
A data frame with 2768 observations on the following 16 variables.
SoldWeek26
a numeric vector, the number of items sold 26 weeks after release and the quantity to predict
StoresSelling1
a numeric vector, the number of stores selling the item 1 week after release
StoresSelling3
a numeric vector
StoresSelling5
a numeric vector
StoresSelling7
a numeric vector
StoresSelling9
a numeric vector
StoresSelling11
a numeric vector
StoresSelling13
a numeric vector
StoresSelling26
a numeric vector, the planned number of stores selling the item 26 weeks after release
Sold1
a numeric vector, the number of items sold 1 week after release
Sold3
a numeric vector
Sold5
a numeric vector
Sold7
a numeric vector
Sold9
a numeric vector
Sold11
a numeric vector
Sold13
a numeric vector, the number of items sold 13 weeks after release
Details
Inspired by the dunnhumby hackathon hosted at https://www.kaggle.com/c/hack-reduce-dunnhumby-hackathon. The goal is to predict the number of items sold 26 weeks after released based on the characteristics of its sales during the first 13 weeks after release (along with information about how many stores are planning to sell the product 26 weeks after release).
Source
Adapted from https://www.kaggle.com/c/hack-reduce-dunnhumby-hackathon