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.

A collection of enhancements to 'ggplot2', with a focus on creating Universally Designed, accessible graphs easily and quickly.

Extensions to 'ggplot2' respecting the grammar of graphics
    paradigm. Statistics to locate and tag peaks and valleys and to label plots
    with the equation of a fitted polynomial model by ordinary least squares,
    major axis, quantile and robust and resistant regression approaches. Line 
    and model equation for Normal mixture models. Labels for P-value, 
    R^2 or adjusted R^2 or information criteria for fitted models; parametric
    and non-parametric correlation; ANOVA table or summary table for fitted 
    models as plot insets; annotations for multiple pairwise
    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, allowing model
    selection and conditional labelling. Scales and stats to 
    build volcano and quadrant plots based on
    outcomes, fold changes, p-values and false discovery rates.

At Novartis, we aimed at standardizing the set of diagnostic plots used for modeling
  activities in order to reduce the overall effort required for generating such plots.
  For this, we developed a guidance that proposes an adequate set of diagnostics and a toolbox,
  called 'ggPMX' to execute them. 'ggPMX' is a toolbox that can generate all diagnostic plots at a quality sufficient
  for publication and submissions using few lines of code. This package focuses on plots recommended by ISoP
  <doi:10.1002/psp4.12161>. While not required, you can get/install the 'R' 'lixoftConnectors'
    package in the 'Monolix' installation, as described at the following url
    <https://monolixsuite.slp-software.com/r-functions/2024R1/installation-and-initialization>.
    When 'lixoftConnectors' is available, 'R' can use 'Monolix' directly to create the required
    Chart Data instead of exporting it from the 'Monolix' gui.