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. …

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, …

Feb 21, 2026 · ggplot(data = mtcars, aes(x = hp)) + geom_histogram(binwidth = 5) + labs(title = "Histogram of Horsepower", x = "Horsepower", y = "Count")

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.

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

Oct 27, 2025 · Exports:.data.expose_data.ignore_data.pt.stroke %+% %+replace% add_gg aes aes_ aes_all aes_auto aes_q aes_string after_scale after_stat alpha annotate annotation_borders …

ggplot() initializes a ggplot object. It can be used to declare the input data frame for a graphic and to specify the set of aesthetic mappings for the plot, intended to be common throughout all subsequent …

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 …