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Documenting functions
Documenting functions
The basics of roxygen2 tags and how to use them for documenting functions.
Examples @examples provides executable R code showing how to use the function in practice. This is a very important part of the documentation because many people look at the examples before reading anything. Example code must work without errors as it is run automatically as part of R CMD check. For the purpose of illustration, it’s often useful to include code that causes an error. You can do this by wrapping the code in try() or using \dontrun{} to exclude from the executed example code. For finer control, you can use @examplesIf: #' @examplesIf interactive() #' browseURL("https://roxygen2.r-lib.org")
Instead of including examples directly in the documentation, you can put them in separate files and use @example path/relative/to/package/root to insert them into the documentation. All functions must have examples for initial CRAN submission.
·roxygen2.r-lib.org·
Documenting functions
Explore Your Data Interactively • ExPanDaR
Explore Your Data Interactively • ExPanDaR
Provides a shiny-based front end (the 'ExPanD' app) and a set of functions for exploratory data analysis. Run as a web-based app, 'ExPanD' enables users to assess the robustness of empirical evidence without providing them access to the underlying data. You can export a notebook containing the analysis of 'ExPanD' and/or use the functions of the package to support your exploratory data analysis workflow. Refer to the vignettes of the package for more information on how to use 'ExPanD' and/or the functions of this package.
·joachim-gassen.github.io·
Explore Your Data Interactively • ExPanDaR
CRAN - Package shinydlplot
CRAN - Package shinydlplot
Add a download button to a 'shiny' plot or 'plotly' that appears when the plot is hovered. A tooltip, styled to resemble 'plotly' buttons, is displayed on hover of the download button. The download button can be used to allow users to download the dataset used for a plot.
·cran.r-project.org·
CRAN - Package shinydlplot
R Scripts in the Google Cloud via Cloud Run, Cloud Build and Cloud Scheduler • googleCloudRunner
R Scripts in the Google Cloud via Cloud Run, Cloud Build and Cloud Scheduler • googleCloudRunner
Tools to easily enable R scripts in the Google Cloud Platform. Utilise cloud services such as Cloud Run for R over HTTP, Cloud Build for Continuous Delivery and Integration services and Cloud Scheduler for scheduled scripts.
·code.markedmondson.me·
R Scripts in the Google Cloud via Cloud Run, Cloud Build and Cloud Scheduler • googleCloudRunner
You're Already Ready: Zen and the Art of R Package Development | Malcolm Barrett
You're Already Ready: Zen and the Art of R Package Development | Malcolm Barrett
R packages make it easier to write robust, reproducible code, and modern tools in R development like usethis make it easy to work with packages. When you write R packages, you also unlock a whole ecosystem of tools that will make it easier to test, document, and share your code. Despite these benefits, many believe package development is too advanced for them or that they have nothing to offer. A fundamental belief in Zen is that you are already complete, that you already have everything you need. I’ll talk about why your project is already an R package, why you’re already an R package deve...
·malco.io·
You're Already Ready: Zen and the Art of R Package Development | Malcolm Barrett