Reshaping Data with the reshape Package

This paper presents the reshape package for R, which provides a common framework for many types of data reshaping and aggregation. It uses a paradigm of 'melting' and 'casting', where the data are 'melted' into a form which distinguishes measured and identifying variables, and then 'cast' into a new shape, whether it be a data frame, list, or high dimensional array. The paper includes an introduction to the conceptual framework, practical advice for melting and casting, and a case study.

The Split-Apply-Combine Strategy for Data Analysis

Many data analysis problems involve the application of a split-apply-combine strategy, where you break up a big problem into manageable pieces, operate on each piece independently and then put all the pieces back together. This insight gives rise to a new R package that allows you to smoothly apply this strategy, without having to worry about the type of structure in which your data is stored. The paper includes two case studies showing how these insights make it easier to work with batting records for veteran baseball players and a large 3d array of spatio-temporal ozone measurements.

Dates and Times Made Easy with lubridate

This paper presents the lubridate package for R, which facilitates working with dates and times. Date-times create various technical problems for the data analyst. The paper highlights these problems and offers practical advice on how to solve them using lubridate. The paper also introduces a conceptual framework for arithmetic with date-times in R.

Data Manipulation with R

Abstracts not available for BookReview

The Split-Apply-Combine Strategy for Data Analysis

Many data analysis problems involve the application of a split-apply-combine strategy, where you break up a big problem into manageable pieces, operate on each piece independently and then put all the pieces back together. This insight gives rise to a new R package that allows you to smoothly apply this strategy, without having to worry about the type of structure in which your data is stored. The paper includes two case studies showing how these insights make it easier to work with batting records for veteran baseball players and a large 3d array of spatio-temporal ozone measurements

A First Course in Statistical Programming with R

Abstracts not available for BookReview

Reshaping Data with the reshape Package

This paper presents the reshape package for R, which provides a common framework for many types of data reshaping and aggregation. It uses a paradigm of 'melting' and 'casting', where the data are 'melted' into a form which distinguishes measured and identifying variables, and then 'cast' into a new shape, whether it be a data frame, list, or high dimensional array. The paper includes an introduction to the conceptual framework, practical advice for melting and casting, and a case study

Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications

Abstracts not available for BookReview