Highlight HTML Text and Tables

A tool to format R markdown with CSS ids for HTML output. The tool may be most helpful for those using markdown to create reproducible documents. The biggest limitations in formatting is the knowledge of CSS by the document authors.

Import an Observable Notebook as HTML Widget

Allows loading and displaying an Observable notebook (online JavaScript notebooks powered by < https://observablehq.com>) as an HTML Widget in an R session, 'shiny' application or 'rmarkdown' document.

Convert 'HTML' to 'R' with a 'Shiny' App

Provides a 'Shiny' app allowing to convert 'HTML' code to 'R' code (e.g. 'Hello' to 'tags$span("Hello")'), for usage in a 'Shiny' UI.

Microplots (Sparklines) in 'LaTeX', 'Word', 'HTML', 'Excel'

The microplot function writes a set of R graphics files to be used as microplots (sparklines) in tables in either 'LaTeX', 'HTML', 'Word', or 'Excel' files. For 'LaTeX', we provide methods for the Hmisc::latex() generic function to construct 'latex' tabular environments which include the graphs. These can be used directly with the operating system 'pdflatex' or 'latex' command, or by using one of 'Sweave', 'knitr', 'rmarkdown', or 'Emacs org-mode' as an intermediary. For 'MS Word', the msWord() function uses the 'flextable' package to construct 'Word' tables which include the graphs. There are several distinct approaches for constructing HTML files. The simplest is to use the msWord() function with argument filetype="html". Alternatively, use either 'Emacs org-mode' or the htmlTable::htmlTable() function to construct an 'HTML' file containing tables which include the graphs. See the documentation for our as.htmlimg() function. For 'Excel' use on 'Windows', the file examples/irisExcel.xls includes 'VBA' code which brings the individual panels into individual cells in the spreadsheet. Examples in the examples and demo subdirectories are shown with 'lattice' graphics, 'ggplot2' graphics, and 'base' graphics. Examples for 'LaTeX' include 'Sweave' (both 'LaTeX'-style and 'Noweb'-style), 'knitr', 'emacs org-mode', and 'rmarkdown' input files and their 'pdf' output files. Examples for 'HTML' include 'org-mode' and 'Rmd' input files and their webarchive 'HTML' output files. In addition, the as.orgtable() function can display a data.frame in an 'org-mode' document. The examples for 'MS Word' (with either filetype="docx" or filetype="html") work with all operating systems. The package does not require the installation of 'LaTeX' or 'MS Word' to be able to write '.tex' or '.docx' files.

Browser-Side Password-Protected HTML Documents

Create secure, encrypted, and password-protected static HTML documents that include the machinery for secure in-browser authentication and decryption.

Convert 'sjPlot' HTML-Tables to R 'data.frame'

A small set of helper functions to convert 'sjPlot' HTML-tables to R data.frame objects / knitr::kable-tables.

Create HTML Content with Bootstrap 5 Classes and Layouts

Functions are pre-configured to utilize Bootstrap 5 classes and HTML structures to create Bootstrap-styled HTML quickly and easily. Includes functions for creating common Bootstrap elements such as containers, rows, cols, navbars, etc. Intended to be used with the html5 package. Learn more at < https://getbootstrap.com/>.

Convert R Markdown Files to DataCamp Light HTML Files

DataCamp Light (< https://github.com/datacamp/datacamp-light>) is a light-weight implementation of the DataCamp UI, that allows you to embed interactive exercises inside HTML documents. The tutorial package makes it easy to create these HTML files from R Markdown files. An extension to knitr, tutorial detects appropriately formatted code chunks and replaces them with DataCamp Light readable chunks in the resulting HTML file.

Generates 'RapiDoc' Documentation from an 'OpenAPI' Specification

A collection of 'HTML', 'JavaScript', 'CSS' and fonts assets that generate 'RapiDoc' documentation from an 'OpenAPI' Specification: < https://mrin9.github.io/RapiDoc/>.

Penalty Learning

Implementations of algorithms from Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression, by Hocking, Rigaill, Vert, Bach < http://proceedings.mlr.press/v28/hocking13.html> published in proceedings of ICML2013.