Streamline the creation of common charts by taking care of a lot of
    data preprocessing and plot customization for the user. Provides a
    high-level interface to create plots using 'ggplot2'.

Provides a Chernoff face geom for 'ggplot2'. Maps multivariate data
    to human-like faces. Inspired by Chernoff (1973) <doi:10.1080/01621459.1973.10482434>.

Provides programmatic implementations for drawing
    Chinese national and historical flags using analytic geometry and
    'ggplot2'-based vector graphics. Flag designs are constructed
    entirely from geometric primitives such as polygons and rectangles,
    without relying on external image files. The package is intended
    for educational demonstration, reproducible visualization, and
    procedural graphics in R.

A function built on 'ggplot2' that visualizes pairwise 'BLAST' alignment results as chord diagrams, intuitively displaying homologous regions between query and subject sequences.

A 'ggplot2' extension that provides functions for drawing chord diagrams for visualising flows between categories. The package extends 'ggplot2' by adding geoms and stats for drawing chord sectors, arcs, and labels.

Provides a 'ggplot2' grammar for circular, axial and directional data, including rose diagrams, circular densities, mean directions, confidence arcs, theoretical circular distributions and movement data visualizations.

Contains the implementation of a binary large margin classifier based on Gabriel Graph. References for this method can be found in L.C.B. Torres et al. (2015) <doi:10.1049/el.2015.1644>.

William S. Cleveland's book 'Visualizing Data' is a classic piece 
	of literature on Exploratory Data Analysis. Although it was written 
	several decades ago, its content is still relevant as it proposes several 
	tools which are useful to discover patterns and relationships among the data 
	under study, and also to assess the goodness of fit o a model.  This package 
	provides functions to produce the 'ggplot2' versions of the visualization tools 
	described in this book and is thought to be used in the context of courses on 
	Exploratory Data Analysis.