A Toolbox for Manipulating and Assessing Colors and Palettes

Carries out mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB, and polar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided along with corresponding ggplot2 color scales. Color palette choice is aided by an interactive app (with either a Tcl/Tk or a shiny graphical user interface) and shiny apps with an HCL color picker and a color vision deficiency emulator. Plotting functions for displaying and assessing palettes include color swatches, visualizations of the HCL space, and trajectories in HCL and/or RGB spectrum. Color manipulation functions include: desaturation, lightening/darkening, mixing, and simulation of color vision deficiencies (deutanomaly, protanomaly, tritanomaly). Details can be found on the project web page at < https://colorspace.R-Forge.R-project.org/> and in the accompanying scientific paper: Zeileis et al. (2020, Journal of Statistical Software, ).

Simple Data Frames

Provides a 'tbl_df' class (the 'tibble') with stricter checking and better formatting than the traditional data frame.

Make Static HTML Documentation for a Package

Generate an attractive and useful website from a source package. 'pkgdown' converts your documentation, vignettes, 'README', and more to 'HTML' making it easy to share information about your package online.

A Simple and Robust JSON Parser and Generator for R

A reasonably fast JSON parser and generator, optimized for statistical data and the web. Offers simple, flexible tools for working with JSON in R, and is particularly powerful for building pipelines and interacting with a web API. The implementation is based on the mapping described in the vignette (Ooms, 2014). In addition to converting JSON data from/to R objects, 'jsonlite' contains functions to stream, validate, and prettify JSON data. The unit tests included with the package verify that all edge cases are encoded and decoded consistently for use with dynamic data in systems and applications.

Easily Create Presentation-Ready Display Tables

Build display tables from tabular data with an easy-to-use set of functions. With its progressive approach, we can construct display tables with a cohesive set of table parts. Table values can be formatted using any of the included formatting functions. Footnotes and cell styles can be precisely added through a location targeting system. The way in which 'gt' handles things for you means that you don't often have to worry about the fine details.

Common S3 Generics not Provided by Base R Methods Related to Model Fitting

In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics.

Render Markdown with 'commonmark'

Render Markdown to full and lightweight HTML/LaTeX documents with the 'commonmark' package. This package has been superseded by 'litedown'.

A 'Linter' for R Code

Checks adherence to a given style, syntax errors and possible semantic issues. Supports on the fly checking of R code edited with 'RStudio IDE', 'Emacs', 'Vim', 'Sublime Text', 'Atom' and 'Visual Studio Code'.

Graph/Network Visualization

Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.

Interpreted String Literals

An implementation of interpreted string literals, inspired by Python's Literal String Interpolation < https://www.python.org/dev/peps/pep-0498/> and Docstrings < https://www.python.org/dev/peps/pep-0257/> and Julia's Triple-Quoted String Literals < https://docs.julialang.org/en/v1.3/manual/strings/#Triple-Quoted-String-Literals-1>.