ggplot2 Themes in R: Customize the Look

Swap themes, kill the grey background, and set panel colours — live in your browser

Learn to restyle a ggplot2 plot in R — switch to a built-in theme (theme_minimal, theme_bw, theme_classic), remove the default grey background, change the panel and plot background colour and grid lines, scale all text with base_size, set a theme for the whole session, and build your own. Edit and run the code live, no install needed.

TipKey takeaways

• A theme controls every non-data element of a plot — background, grid lines, text, ticks, legend — in one place.
• Swap the whole look with one layer: theme_minimal(), theme_bw(), theme_classic(), theme_void(), and more.
• The default grey panel comes from theme_gray(); switch to theme_bw()/theme_classic() (or blank the panel) for a white background.
• Fine-tune any element with theme(...) and the four helpers: element_rect() (backgrounds), element_line() (grids/ticks), element_text() (labels), element_blank() (remove).
• The panel background sits behind the data; the plot background fills the whole image — they are set separately.
• Scale every text label at once with base_size, e.g. theme_minimal(base_size = 16).
• Set a theme for the whole session with theme_set(), or build your own by extending a base theme with %+replace%.
• Every plot below is rendered for you — then tweak any example live in the sandbox.

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Introduction

A ggplot2 theme is the styling layer of your plot: it sets the background colour, the grid lines, the fonts, the axis ticks, and the legend look — everything that isn’t the data itself. The most common search that lands here is “how do I get rid of the grey background?”, and the answer is almost always a theme. In R, ggplot2 ships a gallery of ready-made themes you apply in a single layer, plus a theme() function to override any individual element. This lesson walks through both; the figures are rendered right here, and you can re-run or edit any of them live.

We use the built-in ToothGrowth dataset: the length of odontoblast cells (len) in guinea pigs given vitamin C at three doses (dose: 0.5, 1, or 2 mg/day) via two delivery methods (supp: orange juice OJ or ascorbic acid VC). A grouped box plot gives us plenty of chrome — panel, grid, legend, text — to restyle.

The built-in theme gallery

The fastest way to change a plot’s look is to add a complete theme as a layer. ggplot2 ships several: theme_gray() (the default), theme_bw(), theme_linedraw(), theme_light(), theme_minimal(), theme_classic(), theme_void(), and theme_dark(). Here is the same plot under four of them so you can compare at a glance.

library(ggplot2)
p <- ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length")

# the house default: airy, modern, light gridlines
p + theme_minimal()

Swap theme_minimal() for theme_bw() to get a crisp white panel with a thin border, or theme_classic() for a stripped-back look with only the two axis lines:

library(ggplot2)
p <- ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length")

p + theme_classic()

For richer, hand-tuned third-party themes (Tufte, Economist, WSJ, Stata), the ggthemes package adds a theme_*() family on the same pattern. We keep teaching code on the built-in set — theme_minimal() is the Datanovia house default — but the mechanics below apply to any theme.

Remove the grey background (get a white background)

By far the most common request: the default theme_gray() panel is grey, and you want it white. You have three clean options. The simplest is to switch to a theme that is already white — theme_bw() or theme_classic(). The most surgical is to keep your current theme and blank just the panel background with element_blank().

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme(panel.background = element_blank())

element_blank() is the universal “remove this element” tool — it works on any theme component, not just backgrounds.

Change the panel background colour and grid lines

The panel is the rectangle directly behind your data. Set its colour with panel.background = element_rect(fill = ..., colour = ...), and style the grid lines with panel.grid.major / panel.grid.minor = element_line(...). element_rect() controls rectangular fills and borders; element_line() controls lines.

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme(
    panel.background = element_rect(fill = "#eaf2fb", colour = "grey70"),
    panel.grid.major = element_line(colour = "white", linewidth = 0.6),
    panel.grid.minor = element_line(colour = "white", linewidth = 0.3)
  )

Change the plot background colour

The plot background is the whole image, including the margins around the panel — distinct from the panel itself. Set it with plot.background = element_rect(fill = ...). Colour the two separately to see the difference clearly.

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme(
    plot.background  = element_rect(fill = "#f0f0f0", colour = NA),
    panel.background = element_rect(fill = "white", colour = NA)
  )

Remove the panel border and grid lines

To strip a plot down, blank the grid lines and panel border with element_blank(), then add back the two axis lines with axis.line = element_line(...) — this is essentially how theme_classic() is built.

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme_minimal() +
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    panel.border     = element_blank(),
    axis.line        = element_line(colour = "black")
  )

The four theme element helpers

Every override inside theme() is built from one of four helper functions — learn these and you can style anything:

• element_rect() — rectangles: backgrounds, borders, legend keys (fill, colour, linewidth).
• element_line() — lines: grid lines, axis lines, ticks (colour, linewidth, linetype).
• element_text() — text: titles, axis labels, legend text (colour, size, face, angle).
• element_blank() — removes the element entirely.

Here all four appear in one theme() call:

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme(
    panel.background = element_rect(fill = "#f7f9fc", colour = "grey80"),  # rect
    panel.grid.major = element_line(colour = "#cdd9ea"),                   # line
    axis.title       = element_text(face = "bold", colour = "#1f3a5f"),    # text
    panel.grid.minor = element_blank()                                     # blank
  )

Scale all text at once with base_size

Every built-in theme takes a base_size argument that scales all text — titles, axis labels, tick labels, legend — proportionally. Bump it up for slides or print, drop it for dense dashboards. Pair it with base_family to set the font.

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme_minimal(base_size = 18)

Set a theme for the whole session

Rather than adding a theme to every plot, set a default once with theme_set(). Every subsequent plot uses it until you change it back. Save the old theme first so you can restore it.

library(ggplot2)
old <- theme_set(theme_bw(base_size = 13))   # make theme_bw the default

# no theme layer needed now — it is the session default
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length")

theme_set(old)   # restore the previous default

Build your own custom theme

Once you find a look you like, wrap it in a function so you can reuse it everywhere. Start from a base theme and override a few elements with %+replace%, which replaces whole elements cleanly. This is the pattern behind a house theme like the future theme_datanovia().

library(ggplot2)
theme_house <- function(base_size = 12) {
  theme_minimal(base_size = base_size) %+replace%
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.x = element_blank(),
      axis.title = element_text(face = "bold", colour = "#3a86d4"),
      plot.background = element_rect(fill = "white", colour = NA)
    )
}

ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme_house()

Transparent background

To save a plot with no background — for slides or overlays — blank the panel, plot, and legend rectangles to "transparent" (or use theme_void() for no chrome at all), then tell ggsave() to keep transparency with bg = "transparent".

library(ggplot2)
p <- ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme_minimal() +
  theme(
    panel.background = element_rect(fill = "transparent", colour = NA),
    plot.background  = element_rect(fill = "transparent", colour = NA),
    legend.background = element_rect(fill = "transparent", colour = NA)
  )
p

# to write a transparent PNG to disk, keep the background transparent on save:
# ggsave("plot.png", p, bg = "transparent")

For control over the saved image’s dimensions and resolution, see the saving plots guide.

Black / dark background plot

For a dark dashboard look, hand-build a black panel and plot background, then switch the text and grid to a light colour so it stays readable. theme_dark() gives a grey-dark starting point; this goes fully black.

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", colour = "white", alpha = 0.85) +
  labs(x = "Dose (mg/day)", y = "Tooth length") +
  theme(
    plot.background  = element_rect(fill = "black", colour = NA),
    panel.background = element_rect(fill = "black", colour = NA),
    panel.grid.major = element_line(colour = "grey25"),
    panel.grid.minor = element_blank(),
    axis.text  = element_text(colour = "white"),
    axis.title = element_text(colour = "white")
  )

Try it live

The plots above were rendered at build time. Want to experiment? Edit the code and press Run — it executes in your browser via webR (no server, no install).

Working in Python? A matplotlib styling and stylesheets guide is coming to the Python series.

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Ask Prova “rewrite my theme() call so the plot has a white background and no grid lines” — it answers with code you can run, so the styling is reproducible. The runtime is the judge. Ask Prova →

Frequently asked questions

NoteHow do I remove the grey background in ggplot2?

The grey panel comes from the default theme_gray(). Switch to a theme that is already white — add theme_bw() or theme_classic() as a layer — or keep your theme and blank just the panel with theme(panel.background = element_blank()).

NoteWhat is the difference between panel.background and plot.background?

The panel is the rectangle directly behind your data, set with panel.background; the plot background fills the whole image including the margins around the panel, set with plot.background. They are styled separately, so colouring one does not affect the other.

NoteHow do I make all the text in a ggplot bigger?

Every built-in theme takes a base_size argument that scales all text proportionally — titles, axis labels, tick labels, and legend — at once, e.g. theme_minimal(base_size = 18). Pair it with base_family to also set the font.

NoteHow do I set a default ggplot2 theme for my whole session?

Call theme_set() once, e.g. theme_set(theme_bw()), and every subsequent plot uses it without a per-plot theme layer. Save the current theme first with old <- theme_set(...) so you can restore it later with theme_set(old).

NoteHow do I give a ggplot a transparent background?

Set the panel, plot, and legend rectangles to "transparent" with element_rect(fill = "transparent", colour = NA) inside theme(), then keep the transparency on disk by passing bg = "transparent" to ggsave(). For no chrome at all, start from theme_void().

Test your understanding

ImportantExercise: remove the grey background

Complete the code so the plot has a clean white background instead of the default grey panel.

# A single built-in theme layer does it — try theme_bw() or theme_classic().

library(ggplot2) ggplot(ToothGrowth, aes(x = factor(dose), y = len)) + geom_boxplot(fill = "#3a86d4", alpha = 0.7) + theme_bw()

library(ggplot2)
ggplot(ToothGrowth, aes(x = factor(dose), y = len)) +
  geom_boxplot(fill = "#3a86d4", alpha = 0.7) +
  theme_bw()

Conclusion

You restyled a ggplot2 plot by swapping built-in themes, removed the default grey background for a clean white one, set the panel and plot background colours and grid lines, used the four element_*() helpers, scaled all text with base_size, set a session-wide default with theme_set(), and wrapped your own look in a reusable custom theme. Styling the data colours (palettes, scale_fill_*) lives in the colours guide, and legend placement and styling in the legend guide. Next, apply these themes to the rest of the ggplot2 grammar.

Related lessons

• Colours & palettes — palettes that pair with a theme. · Legend — legend placement and style. · Titles, subtitles & captions — the text a theme styles. · Facets — style multi-panel strips.
• Use it on: boxplot · histogram · scatter plot · bar plot · line plot. · ggplot2 — the full series. · Data Visualization — the pillar.

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Note

This lesson is reproducible: the figures are executed at build time (if they render, the code works), and the sandbox + quiz re-run live in your browser. The runtime is the judge.