EDS 240: Discussion 4

Recreating US Drought Monitor viz

Part 2: ggplot themes

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Week 4 | January 27^th, 2024

Themes modify non-data plot elements

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Themes are used to modify the non-data components of plots (e.g. titles, labels, fonts, background, gridlines, legend).

In addition to using pre-built themes (available via the {ggplot2} package and also from extension packages), you can fine-tune the appearance of your plots theme by making adjustments using the theme() function.

Pre-built themes

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{ggplot2} comes with eight complete themes, which can be applied as-is, or further modified using theme(). There are also many additional themes which can be applied via ggplot extension packages. A small handful of packages with additional themes:

• {ggthemes}: a collection of popular themes, some of which also come with corresponding color scales
• {hrbrthemes}: typographic-centric themes and theme components -{ggthemr}: a collection of color palettes and plot layouts for quickly setting a ggplot theme
• {ggtech}: themes based off large tech company color palettes
• {ggdark}: dark mode for ggplot complete themes
• {firatheme}: a ggplot theme with Fira font
• {urbnthemes}: tools for creating Urban Institute-themed plots and maps in R (also check out the Urban Institute Data Visualization Style Guide for a really great example of how an organization enforces a cohesive style across all published data viz content)
• {bbplot}: tools for creating ggplots in the style used by the BBC News data team
• {ggpomological}: a ggplot2 theme based on the USDA Pomological Watercolor Collection
• {tvthemes}: a collection of ggplot themes and color / fill palettes based on everybody’s favorite TV shows

Keep an eye out for plot-specific themes

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Keep your eye out for extension packages that supply both a geom(s) and a pre-build theme(s) designed specifically to work with that geom. For example, the {ggridges} package provides both a few different ridgeline plot geoms and a pre-built theme_ridges() theme to pair with them:

Use ggplot2::theme() for fine-tune control

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Recreate this USDM plot

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Reference the graphic on the previous slide (and of course, documentation – run ?theme or check out online documentation) to start tweaking plot elements until it matches the original USDM graphic (below). It’s common to start with a pre-built theme and modify from there.