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 …

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 …

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 …

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 …

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, …

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.

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

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 …

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 …