However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()). You then add on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), …

plotly: turn your ggplot interactive Another awesome feature of ggplot2 is its link with the plotly library. If you know how to make a ggplot2 chart, you are 10 seconds away to rendering an interactive version. …

A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes …

However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()). You then add on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), …

Nov 24, 2025 · A curated ggplot2 hub for R. Learn geoms, axes/scales, labels/annotations, themes, faceting, colors, and saving plots—each with working code and examples.

However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()). You then add on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), …

Jul 23, 2025 · The `aes ()` function in ggplot stands for aesthetic mappings. It is used to map variables in your data to visual properties of the plot like position, color, size, shape, etc.

Plots may be created via the convenience function qplot() where arguments and defaults are meant to be similar to base R's plot() function. [19][20] More complex plotting capacity is available via ggplot() …

You’ll learn the basics of ggplot() along with some useful “recipes” to make the most important plots. ggplot() allows you to make complex plots with just a few lines of code because it’s based on a rich …

Geoms Use a geom function to represent data points, use the geom’s aesthetic properties to represent variables. Each function returns a layer. Graphical Primitives a <- ggplot(economics, aes(date, …