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Visualizing data can be the most engaging way to tell a story, reveal insights, and communicate complex information. When it comes to creating stunning, layered plots in R, ggplot2 is the go-to tool. Part of the tidyverse collection, ggplot2 stands out not only for its flexibility and visual appeal but also for the grammar-based approach it offers. This grammar of graphics framework makes it intuitive to combine various components-like points, lines, shapes, and facets-to create richly informative plots.
You can find the code used in this post below 👇
What’s Special About ggplot2?
At its core, ggplot2 is structured around a series of layers. Each layer represents a different part of the plot, like data, geometries, and statistical transformations. This makes it incredibly flexible-you can start with a simple scatter plot and layer in colors, labels, and even transformations until you have exactly the visualization you need.
Another reason to love ggplot2 is its elegance with data mapping. Instead of manually coding each feature, you define a mapping of variables to visual properties, such as color, size, and shape. The rest is taken care of by ggplot2, which…
