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()), faceting specifications (like facet_wrap()) and …

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 …

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

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()), faceting specifications (like facet_wrap()) and …

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 care of the details.

Plots may be created via the convenience function qplot() where arguments and defaults are meant to be similar to base R's plot() function. [18][19] More complex plotting capacity is available via ggplot() which exposes the user to more explicit elements of the grammar.

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 to the ggplot() itself or can be supplied to respective geoms. More on that later.

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.

Jun 25, 2025 · Image by Editor | Midjourney Customizing ggplot2 themes in R helps you create visuals that match your brand. You can change things like colors, fonts, and layout to make your plots look consistent. ggplot2 offers many options to adjust the style of your graphs. This lets you create professional and unique visuals that fit your brand. In this guide, we’ll show you how to …