Complete Themes: Styling Your Plots for a Cohesive Look

Themes control the overall style of your plots — from typefaces and font settings to grid lines, backgrounds, and margins. They’re what make a chart feel clean, polished, and consistent.

In this lesson, you’ll learn how to apply and adjust complete themes to give your plots a cohesive look without touching the underlying data or mappings. By the end, you’ll know how to switch between built-in themes, customize them, and make your charts presentation-ready with just a few lines of code.

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👗 Change Your Style

Back in the principles lesson, we introduced themes as one of the main ggplot2 components. Unlike aesthetics, layers, scales, or coordinate systems, themes don’t affect what data is shown or how it’s mapped.

→Themes style non–data ink. They won’t change values, mappings, or geoms — only how the plot looks.

Themes are a different kind of component: they act as the “finishing layer” of your visualization and focus entirely on styling and presentation. Typefaces, font styles, legends, backgrounds, grid lines, margins — all of these can be controlled with themes to make your charts look clean and polished without touching the underlying data.

We saved themes for this Customization & Styling module on purpose: once you’re comfortable building plots from data, themes let you give them a cohesive look to make it publication-ready — simply swap a complete theme and or nudge a few elements to add a custom and personal touch.

🎨 Themes at a Glance

The fastest way to style your plot is by applying a complete theme .

A theme is simply a pre-built set of settings that control everything—from background colors and grid lines to text and spacing. With just one extra line of code, you get a clean, consistent style to build on.

Here’s an example using the minimal theme:

Note: By default, every ggplot starts with the complete theme theme_grey(), which adds the classic “corporate grey” look. That’s a solid baseline — but it can feel a bit… well, ggplot-y.

🌍 A World of Themes

ggplot2 📦 comes with a set of complete themes to cover common needs.

Beyond that, the community has created packages with additional ready-to-use themes, such as ggthemes, hrbrthemes, and tvthemes.

Some replicate the visual styles of well-known companies, newspapers, or software, while others take a more playful approach—referencing popular TV shows and other bits of pop culture.

As always, here’s a little explorer to see if you can find a theme you like!

ggplot2

theme_gray

theme_bw

theme_minimal

theme_light

theme_classic

theme_dark

theme_void

hrbrthemes

theme_ipsum

theme_ft_rc

theme_modern_rc

ggthemes

theme_economist

theme_few

theme_tufte

theme_wsj

theme_stata

theme_excel

theme_solarized

theme_hc

theme_base

theme_calc

theme_map

tvthemes

theme_avatar

theme_brooklyn99

theme_hildaDay

theme_parksAndRec

theme_rickAndMorty

theme_simpsons

theme_spongeBob

📡 Hello, Base

→base_line_size and base_rect_size also exist, but as these scale with base_size, you’ll rarely need to touch them.

When applying a complete theme, two arguments are especially handy:base_size and base_family. They let you adjust the base settings in one go.

base_size sets the overall scale of all theme elements
base_family defines the typeface for all text elements.

This way, you don’t need to repeat those settings for each element to change the overall readability and character of a plot: adjusting text size and typeface alone can already make a chart feel more professional, playful, or simply easier to read in context.

Which Fonts Can I Use in base_family?

While you can only specify the universal font families in our sandboxes — "sans" (default), "serif", and "monospace" — you’re not limited to these in your own setup. Any installed font can be applied to your ggplot themes using base_family.

For example, the font we use for the body text of this course, Domine, can be installed locally and then referenced in your themes by its family name:

ggplot(mpg, aes(x = class)) +
  geom_bar() +
  theme_minimal(base_family = "Domine")

We will talk about using non-default typefaces a lot more in upcoming lessons. For a detailed guide on using custom fonts in R and applying them in your plots, see the Custom Themes lesson.

🐇 Going Down the Rabbit Hole

Adjusting the base settings of a complete theme won’t affect colors or the layout of individual elements. That’s where the theme() function comes in: in the next lesson, you’ll learn how to fine-tune your plots in detail — from changing the typeface of a specific text element, to tweaking grid lines and margins, to moving the legend exactly where you want it.

Still, complete themes, whether built into ggplot2 or provided by extension packages, already give you a strong foundation. And if you prefer to keep things simple, you can stick with those plus a few base settings for clean, polished plots without much extra effort.

🏆 Exercises

There is nothing too complicated in this lesson. But let’s practice a little to make sure those concepts stick in your head.

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Project

Custom Themes