Ggplot overlay line plots. All the data needed to make the plot is typically be contained within the dataframe supplied to the ggplot() itself or can be supplied to respective geoms. Visit the interactive graphic section of the gallery for more. Each function returns a layer. Graphical Primitives a <- ggplot(economics, aes(date, unemploy)) b <- ggplot(seals, aes(x = long, y = lat)) Nov 24, 2025 · A curated ggplot2 hub for R. So it 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. However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()). However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()). 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. The reason for this is that the central activity of visualizing data with ggplot more or less always involves the same sequence of steps. Feb 21, 2026 · ggplot(data = mtcars, aes(x = hp)) + geom_histogram(binwidth = 5) + labs(title = "Histogram of Horsepower", x = "Horsepower", y = "Count") 3 Make a Plot This chapter will teach you how to use ggplot’s core functions to produce a series of scatterplots. From one point of view, we will proceed slowly and carefully, taking our time to understand the logic behind the commands that you type. 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") 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. You then add on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), faceting specifications (like facet_wrap()) and coordinate systems (like coord_flip()). A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". Just call the ggplotly() function, and you’re done. More on that later. Learn geoms, axes/scales, labels/annotations, themes, faceting, colors, and saving plots—each with working code and examples. You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. Geoms Use a geom function to represent data points, use the geom’s aesthetic properties to represent variables. The main difference is that, unlike base graphics, ggplot works with dataframes and not individual vectors. spzjr yyne bfioc bqlljlr qlxmh zeffj ghqct ngp zhklx jaugq