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Data Visualizations with ggplot2 in R

Additional Themes in ggplot2

Discover how to apply a variety of additional themes from the ggthemes and ggdark packages to customize ggplot2 plots. Explore popular styles inspired by FiveThirtyEight, The Economist, and Stata, including dark themes for improved readability in low-light settings.

We'll cover the following...

Additional themes available for ggplot2

In addition to the built-in themes provided by ggplot2, several libraries offer additional themes helpful to customize the appearance of plots. These libraries include ggthemes, ggdark, ggtech, ggthemr, and hrbrthemes, which provide a wide range of themes with different visual styles and color palettes.

We’ll discuss two of these libraries in detail and how to use their themes in ggplot2 plots with examples. We can add more variety and customization to our plots using these additional themes.

Let’s first create a density plot using the iris dataset and then explore the additional themes in ggplot2:

R
chart<-ggplot(iris) +
  geom_density(aes(x = Sepal.Length, fill=Species),
    alpha=0.6)
chart
  • Line 1: We create a new object named chart and use the assignment operator <- for storing the graph in the chart object. We initialize a new ggplot object with the ggplot() function and pass the name of the iris dataset. Using the + operator, we add a layer to the ggplot object.
  • Line 2: We use the geom_density() function to create a density plot. Next, we use the aes() function for mapping the Sepal.Length
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