Provides interactive visualisations for exploratory data analysis of high-dimensional datasets.
  Includes parallel coordinate plots for exploring large datasets with mostly quantitative features, 
  but also stacked one-dimensional visualisations that more effectively show missingness and complex categorical relationships in smaller datasets.

Compute marginal effects and adjusted predictions from statistical
    models and returns the result as tidy data frames. These data frames are
    ready to use with the 'ggplot2'-package. Effects and predictions can be
    calculated for many different models. Interaction terms, splines and
    polynomial terms are also supported. The main functions are ggpredict(),
    ggemmeans() and ggeffect(). There is a generic plot()-method to plot the
    results using 'ggplot2'.

Methods for searching through genealogical data and displaying the results. Plotting algorithms assist with data exploration and publication-quality image generation. Includes interactive genealogy visualization tools. Provides parsing and calculation methods for variables in descendant branches of interest. Uses the Grammar of Graphics.

Audits 'ggplot2' visualizations for accessibility issues, misleading 
    practices, and readability problems. Checks for color accessibility concerns 
    including colorblind-unfriendly palettes, misleading scale manipulations such 
    as truncated axes and dual y-axes, text readability issues like small fonts 
    and overlapping labels, and general accessibility barriers. Provides 
    comprehensive audit reports with actionable suggestions for improvement.
    Color vision deficiency simulation uses methods from the 'colorspace' 
    package Zeileis et al. (2020) <doi:10.18637/jss.v096.i01>. Contrast 
    calculations follow WCAG 2.1 guidelines (W3C 2018 
    <https://www.w3.org/WAI/WCAG21/Understanding/contrast-minimum>).

Extension of 'ggplot2' providing layers, scales and preprocessing functions
    useful to represent behavioural variables that are recorded over multiple animals and days.
    This package is part of the 'rethomics' framework <https://rethomics.github.io/>.