collapse Documentation and Resources

collapse is a C/C++ based package for data transformation and statistical computing in R. It’s aims are:

To facilitate complex data transformation, exploration and computing tasks in R.
To help make R code fast, flexible, parsimonious and programmer friendly.

Documentation comes in 6 different forms:

Built-In Structured Documentation

After installing collapse, you can call help("collapse-documentation") which will produce a central help page providing a broad overview of the entire functionality of the package, including direct links to all function documentation pages and links to 13 further topical documentation pages (names in .COLLAPSE_TOPICS) describing how clusters of related functions work together.

Thus collapse comes with a fully structured hierarchical documentation which you can browse within R - and that provides everything necessary to fully understand the package. The Documentation is also available online.

The package page under help("collapse-package") provides some general information about the package and its design philosophy, as well as a compact set of examples covering important functionality.

Reading help("collapse-package") and help("collapse-documentation") is the most comprehensive way to get acquainted with the package. help("collapse-documentation") is always the most up-to-date resource.

Cheatsheet

An up-to-date (v2.0) cheatsheet compactly summarizes the package.

Article on arXiv

An article on collapse (v2.0.10) has been submitted to the Journal of Statistical Software in March 2024.

useR 2022 Presentation and Slides

I have presented collapse (v1.8) in some level of detail at useR 2022. A 2h video recording that provides a quite comprehensive introduction is available here. The corresponding slides are available here.

Vignettes

Updated vignettes are

collapse for tidyverse Users: A quick introduction to collapse for tidyverse users
collapse and sf: Shows how collapse can be used to efficiently manipulate sf data frames
collapse’s Handling of R Objects: A quick view behind the scenes of class-agnostic R programming

The other vignettes (only available online) do not cover major features introduced in versions >= 1.7, but contain much useful information and examples:

Introduction to collapse : Introduces key features in a structured way
collapse and dplyr : Demonstrates the integration of collapse with dplyr / tidyverse workflows and associated performance improvements
collapse and plm: Demonstrates the integration of collapse with plm and shows examples of efficient programming with panel data
collapse and data.table: Shows how collapse and data.table may be used together in a harmonious way

Blog

I maintain a blog linked to Rbloggers.com where I introduced collapse with some compact posts covering central functionality. Among these, the post about programming with collapse is useful for developers.

Sebastian Krantz

2024-11-03