Reason 7 Powerful data visualization
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Perhaps the most popular package for data visualization in R is
{ggplot2}. It comes with the {tidyverse}
package, but there are many other packages that extend the functionality of {ggplot2},
such as {ggforce} or {gganimate}.
These packages share a unifying design principle, the Grammar of Graphics (hence the “gg”). At its core, the Grammar of Graphics is about mapping attributes of your data (such as the magnitude of a number or the category that an observation belongs to) to aesthetics of geometric objects (such as position and size of a point or the height and color of a bar), potentially after applying statistical transformations like counting or averaging observations. This foundation turns out to be extremely versatile and allows
You can see examples of what is possible with {ggplot2} in the submissions for Tidy
Tuesday – a weekly exercise for practicing
data visualisation. Some people even use {ggplot2} to make generative
Art!
Mastering {ggplot2} can take a while. However, there are some websites that provide
example code for different types of charts. The R graph
gallery is particularly comprehensive. There
are also packages like
{esquisse}
that provide you with an intuitive graphical user interface for using {ggplot2}.
The {ggplot2} package itself is mainly limited to static graphs. However, packages like
{plotly}, and {shiny}
allow you to make interactive visualizations and dashboards with relative ease.
Integration with JavaScript (e.g., D3.js) - the sky
is the limit!
See ggplot2 – Elegant graphics for data analysis for a deep
dive into {ggplot2}
7.1 The fastest way to make a plot
In a short intro like this, there is not enough time to dive deeply into {ggplot2}.