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. …

Jul 12, 2025 · ggplot(data = mtcars, aes(x = hp, y = mpg, col = disp))+ labs(title = "MTCars Data Plot")

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 …

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.

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, …

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()), …

Check the full list of charts made with ggplot2 and learn how to customize the plots customizing the axes, the background color, the themes and others

As the first step in many plots, you would pass the data to the ggplot() function, which stores the data to be used later by other parts of the plotting system.

A while ago I reluctantly decided that there is no rationale for me to learn ggplot. I still believe so. And yet, here I am, desperately resisting temptation. Two guys I admire, and a course that looks brilliant. …