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 …

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 …

Jul 12, 2025 · ggplot(data = mtcars, aes(x = hp, y = mpg)) + geom_point() + facet_grid(am ~ cyl) + theme_gray()+ labs(title = "Miles per Gallon vs Horsepower")

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 …

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 …

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 …

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. For example, if we intend to make a …

In order to create a plot, you: Call the ggplot() function which creates a blank canvas Specify aesthetic mappings, which specifies how you want to map variables to visual aspects. In this …