Unified Data Visualization Framework for Dynamic and Static Graphics

Provides a unified API for creating data visualizations across dynamic and static rendering modes. Visualizations are defined once using a specification object and can be rendered with 'highcharter', 'ggplot2', or other supported packages without modifying user code. The package supports declarative and layered workflows, reusable themes and colour palettes, optional 'JavaScript' enhancements, export tools, and interactive exploration through 'shiny' applications.

Command Line Interface Plotting

The 'plotcli' package provides terminal-based plotting in R. It supports colored scatter plots, line plots, bar plots, boxplots, histograms, density plots, and more. The 'ggplotcli()' function is a universal converter that renders any 'ggplot2' plot in the terminal using Unicode Braille characters or ASCII. Features include support for 15+ geom types, faceting (facet_wrap/facet_grid), automatic theme detection, legends, optimized color mapping, and multiple canvas types.

Freshing Up your 'ggplot2' Plots

Functions for working with legends and axis lines of 'ggplot2', facets that repeat axis lines on all panels, and some 'knitr' extensions.

Tidy Tools for Paleoenvironmental Archives

Provides a set of functions with a common framework for age-depth model management, stratigraphic visualization, and common statistical transformations. The focus of the package is stratigraphic visualization, for which 'ggplot2' components are provided to reproduce the scales, geometries, facets, and theme elements commonly used in publication-quality stratigraphic diagrams. Helpers are also provided to reproduce the exploratory statistical summaries that are frequently included on stratigraphic diagrams. See Dunnington et al. (2021) .

KMunicate-Style Kaplan–Meier Plots

Produce Kaplan–Meier plots in the style recommended following the KMunicate study by Morris et al. (2019) . The KMunicate style consists of Kaplan-Meier curves with confidence intervals to quantify uncertainty and an extended risk table (per treatment arm) depicting the number of study subjects at risk, events, and censored observations over time. The resulting plots are built using 'ggplot2' and can be further customised to a certain extent, including themes, fonts, and colour scales.

Hacks for 'ggplot2'

A 'ggplot2' extension that does a variety of little helpful things. The package extends 'ggplot2' facets through customisation, by setting individual scales per panel, resizing panels and providing nested facets. Also allows multiple colour and fill scales per plot. Also hosts a smaller collection of stats, geoms and axis guides.

R Templates for Reproducible Data Analyses

A collection of R Markdown templates for nicely structured, reproducible data analyses in R. The templates have embedded examples on how to write citations, footnotes, equations and use colored message/info boxes, how to cross-reference different parts/sections in the report, provide a nice table of contents (toc) with a References section and proper R session information as well as examples using DT tables and ggplot2 graphs. The bookdown Lite template theme supports code folding.

A Grammar of Data Manipulation

A fast, consistent tool for working with data frame like objects, both in memory and out of memory.

Manage Branding and Accessibility of R Projects

A tool for building projects that are visually consistent, accessible, and easy to maintain. It provides functions for managing branding assets, applying organization-wide themes using 'brand.yml', and setting up new projects with accessibility features and correct branding. It supports 'quarto', 'shiny', and 'rmarkdown' projects, and integrates with 'ggplot2'. The accessibility features are based on the Web Content Accessibility Guidelines < https://www.w3.org/WAI/WCAG22/quickref/?versions=2.1> and Accessible Rich Internet Applications (ARIA) specifications < https://www.w3.org/WAI/ARIA/apg/>. The branding framework implements the 'brand.yml' specification < https://posit-dev.github.io/brand-yml/>.

Style Time Series Plots Like the Wall Street Journal

Easily override the default visual choices in 'ggplot2' to make your time series plots look more like the Wall Street Journal. Specific theme design choices include omitting x-axis grid lines and displaying sparse light grey y-axis grid lines. Additionally, this allows to label the y-axis scales with your units only displayed on the top-most number, while also removing the bottom most number (unless specifically overridden). The goal is visual simplicity, because who has time to waste looking at a cluttered graph?