Note: since R 3.0.0, you can build Markdown vignettes naturally; see https://yihui.org/knitr/demo/vignette/ for details.
What is the best resource to learn an R package? Many R users know the almighty question mark
? in R. For example, type
?lm and you will see the documentation of the function
lm. If you know nothing about a package, you can take a look at the HTML help by
where you can find the complete list of documentation by clicking the link
Packages. The individual help pages are often boring and difficult to read, because you cannot see the whole picture of the elephant. That is where package vignettes can help a lot. A package vignette is like a short paper (in fact some are real journal papers), which gives you an overview of this package, and sometimes with examples. Package vignettes are not a required component of an R package, so you may not find them in all packages. For those packages which contain vignettes, you can find them by
browseVignettes(), e.g. for the knitr package
browseVignettes(package = 'knitr') # or go to system.file('doc', package = 'knitr')
You can also see links to vignettes from
Packages and go to the package documentation, or
help.start() browseURL(paste0('http://127.0.0.1:', tools:::httpdPort(), '/library/knitr/doc/index.html'))
Most vignettes are written in LaTeX/Sweave since that is the official approach (see Writing R Extensions). In the past Google Summer of Code, Taiyun Wei explored a few interesting directions of the knitr package, and one of them was to build HTML vignettes for R packages from Markdown, which is much easier to write than LaTeX.
For package authors who are interested, Taiyun’s corrplot package (on Github) can serve as an example. The markdown vignette is vignettes/corrplot-intro.Rmd. When you run
R CMD build corrplot,
corrplot-intro.Rmd will be converted to
corrplot-intro.html, which you can view in
R CMD INSTALL corrplot_*.tar.gz.
Once you have this HTML vignette, you can also publish it elsewhere. For example, either RPubs.com or GitHub pages to gain more publicity (see an example of the phyloseq package). It is important to let users be aware of package vignettes, and a web link is apparently easier to tell other people than
browseVignettes() (I felt very uncomfortable when I was writing the first half of this post because the vignettes are hidden so deep, hence so hard to describe).
So why not start building an HTML vignette for your package with R Markdown now? Think about animations, interactive content (e.g. googleVis), MathJax equations and other exciting web stuff.