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()), …

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, …

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.

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()), …

The main difference is that, unlike base graphics, ggplot works with dataframes and not individual vectors. All the data needed to make the plot is typically be contained within the dataframe supplied …

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

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

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() …

For greater control, use ggplot () and other functions provided by the package. Note that ggplot2 functions can be chained with "+" signs to generate the final plot.