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 is forthcoming at Journal of Statistical Software.

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
Developing with collapse: How to write efficient statistical packages using R and collapse

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

2025-10-24