Provides various themes, palettes, and other functions
    that are used to customise ggplots to look like they were made in 'GraphPad 
    Prism'. The 'Prism'-look is achieved with theme_prism() and 
    scale_fill|colour_prism(), axes can be changed with custom guides like 
    guide_prism_minor(), and significance indicators added with add_pvalue().

Provides 'ggplot2' coordinates, layers, scales, themes, and presets for
    creating psychrometric charts. The package supports metric and inch-pound
    unit systems, psychrometric grids, state points, process lines, zones, and
    thermal comfort overlays for heating, ventilation, air conditioning, and
    building performance workflows. Psychrometric property calculations are
    based on 'PsychroLib' (Meyer and Thevenard, 2019)
    <doi:10.21105/joss.01137> where appropriate.

The 'ggplot2' package is excellent and flexible for elegant data
    visualization in R. However the default generated plots require some formatting
    before we can send them for publication. Furthermore, to customize a 'ggplot',
    the syntax is opaque and this raises the level of difficulty for researchers
    with no advanced R programming skills. 'ggpubr' provides some easy-to-use
    functions for creating and customizing 'ggplot2'-based publication ready plots.
    This version includes modern R ecosystem compatibility updates and customizable
    p-value formatting presets (APA, AMA, NEJM, Lancet, GraphPad, and scientific
    notation) for publication workflows, plus robust sparse-subset handling in
    statistical annotation layers such as 'stat_compare_means()' and 'geom_pwc()',
    with informative per-group skip diagnostics for non-comparable subsets.

Automatically performs desired statistical tests (e.g. wilcox.test(), t.test()) to compare between groups, 
    and adds the resulting p-values to the plot with an annotation bar.
    Visualizing group differences are frequently performed by boxplots, bar plots, etc.
    Statistical test results are often needed to be annotated on these plots. 
    This package provides a convenient function that works on 'ggplot2' objects, 
    performs the desired statistical test between groups of interest and annotates the test results on the plot.