SOLD26: Predicting future sales
In profpetrie/regclass: Tools for an Introductory Class in Regression and Modeling
Description
Usage
Format
Details
Source
Description
Predicting future sales based on sales data in first quarter after release
Usage
1
data("SOLD26")
Format
A data frame with 2768 observations on the following 16 variables.
SoldWeek26a numeric vector, the number of items sold 26 weeks after release and the quantity to predict
StoresSelling1a numeric vector, the number of stores selling the item 1 week after release
StoresSelling3a numeric vector
StoresSelling5a numeric vector
StoresSelling7a numeric vector
StoresSelling9a numeric vector
StoresSelling11a numeric vector
StoresSelling13a numeric vector
StoresSelling26a numeric vector, the planned number of stores selling the item 26 weeks after release
Sold1a numeric vector, the number of items sold 1 week after release
Sold3a numeric vector
Sold5a numeric vector
Sold7a numeric vector
Sold9a numeric vector
Sold11a numeric vector
Sold13a 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
profpetrie/regclass documentation built on May 26, 2019, 8:33 a.m.
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Description Usage Format Details Source
Description
Predicting future sales based on sales data in first quarter after release
Usage
1 | data("SOLD26")
|
Format
A data frame with 2768 observations on the following 16 variables.
SoldWeek26a numeric vector, the number of items sold 26 weeks after release and the quantity to predict
StoresSelling1a numeric vector, the number of stores selling the item 1 week after release
StoresSelling3a numeric vector
StoresSelling5a numeric vector
StoresSelling7a numeric vector
StoresSelling9a numeric vector
StoresSelling11a numeric vector
StoresSelling13a numeric vector
StoresSelling26a numeric vector, the planned number of stores selling the item 26 weeks after release
Sold1a numeric vector, the number of items sold 1 week after release
Sold3a numeric vector
Sold5a numeric vector
Sold7a numeric vector
Sold9a numeric vector
Sold11a numeric vector
Sold13a 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
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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