# collapse Documentation and Resources

#### 2023-01-24

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

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

Documentation comes in 5 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.

## useR 2022 Presentation and Slides

I have presented collapse in detail at useR 2022. A 2h video recording that provides a quite comprehensive up-to-date introduction is available here. The corresponding slides are available here.

## Cheatsheet

There is an updated (2022) cheatsheet that compactly summarizes the package.

## Vignettes

There are also 5 vignettes which are available online (due to their size and the enhanced browsing experience on the website). The vignettes are:

• 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

• collapse and sf: Shows how collapse can be used to efficiently manipulate sf data frames

Note that these vignettes currently do not cover major features introduced in versions 1.7 through 1.9. They have been updated if you see a 2023 in the date of the vignette. Updating them is currently not a priority for me, but you are welcome to help update them.

## 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 ambitious users and developers willing to build on collapse.