This guide walks through the process of developing an R package

This is an example of writing an R package using the Literate Programming (LP) technique, implemented through the knitr package and Makefile. It only shows you the idea, and I do not mean you must use …

This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other documents or chunks, control the formatting with customer templates, fine-tune how your code is processed, and incorporate multiple languages into your analysis.

As organizations grow and mature, so does the organization’s data. Eventually, the data may become too ‘big’ or too complicated for…

Learn step-by-step how to built a wedding risk model Shiny app.

This is official open data science training for the Ocean Health Index.

Using Git and GitHub with R, Rstudio, and R Markdown

Turn your analyses into high quality documents, reports, presentations and dashboards with R Markdown. Use a productive notebook interface to weave together narrative text and code to produce elegantly formatted output. Use multiple languages including R, Python, and SQL. R Markdown supports a reproducible workflow for dozens of static and dynamic output formats including HTML, PDF, MS Word, Beamer, HTML5 slides, Tufte-style handouts, books, dashboards, shiny applications, scientific articles, websites, and more.

The first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages.

The printr (read “printer” or “print R”) package is a companion package to knitr. Its main purpose is to extend the S3 generic function knit_print() in knitr, which is the …

Data documentation in psychology lags behind not only many other disciplines, but also basic standards of usefulness. Psychological scientists often prefer to i...

Access and manipulate Microsoft Word and Microsoft PowerPoint documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. The package does not require any installation of Microsoft products to be able to write Microsoft files.

Learn how to get started with the basics of pkgdown.

Rmarkdown for Scientists. Contribute to njtierney/rmd4sci development by creating an account on GitHub.

Improving the track changes and reviewing experience in R markdown - ropenscilabs/reviewer

Lightweight infrastructure to handle multiple rmarkdown reports - reconhub/reportfactory

Automated checking of best practices for research compendia ✔️ - ropenscilabs/checkers

R package containing a collection of Rmarkdown templates - Pakillo/rmdTemplates

🔑 Password protected markdown html reports in R using libsodium - dirkschumacher/encryptedRmd

R package :package: for labelling chunks of RMarkdown files! :boom: - lockedata/namer

A workflow for refactoring one-time analyses to sustainable data products