Selected utilities, in particular 'geoms' and 'stats'
    functions, extending the 'ggplot2' package. This package imports
    functions from 'EnvStats' <doi:10.1007/978-1-4614-8456-1> by Millard
    (2013), 'ggpp' <https://CRAN.R-project.org/package=ggpp> by Aphalo et
    al. (2023) and 'ggstats' <doi:10.5281/zenodo.10183964> by Larmarange
    (2023), and then exports them. This package also contains modified
    code from 'ggquickeda' <https://CRAN.R-project.org/package=ggquickeda>
    by Mouksassi et al. (2023) for Kaplan-Meier lines and ticks additions
    to plots.  All functions are tested to make sure that they work
    reliably.

A dataset about movies. This was previously contained in ggplot2,
   but has been moved its own package to reduce the download size of ggplot2.

An 'RStudio' addin for teaching and learning making plot using the 'ggplot2' package.
    You can learn each steps of making plot by clicking your mouse without coding.
    You can get resultant code for the plot.

Easily explore data by creating ggplots through a (shiny-)GUI. R-code to recreate graph provided.

Convert plot function call (using expression or formula) to 'grob' or 'ggplot' object that compatible to the 'grid' and 'ggplot2' ecosystem. With this package, we are able to e.g. using 'cowplot' to align plots produced by 'base' graphics, 'ComplexHeatmap', 'eulerr', 'grid', 'lattice', 'magick', 'pheatmap', 'vcd' etc. by converting them to 'ggplot' objects.

Extensions to 'ggplot2' respecting the grammar of graphics
    paradigm. Statistics: locate and tag peaks and valleys; label plot with the
    equation of a fitted polynomial or other types of models including major
    axis, quantile and robust and resistant regression. Labels for P-value, 
    R^2 or adjusted R^2 or information criteria for fitted models; parametric
    and non-parametric correlation; label with ANOVA table for fitted models; 
    label with summary table for fitted models; annotations for multiple 
    comparisons with adjusted P-values. Model fit classes for which suitable 
    methods are provided by package 'broom' and 'broom.mixed' are supported as 
    well as user-defined wrappers on model fit functions. Scales and stats to build volcano and quadrant plots based on
    outcomes, fold changes, p-values and false discovery rates.