Write your ggplot2 theme once, use it everywhere

A ten-line theme function is the cheapest branding investment an analytics team can make. Here is ours, and how to set it as a session default.

Open any report produced by a team without a shared plotting theme and you can tell which analyst made which figure — different fonts, different greys, different grid lines. The fix is a theme function: written once, applied everywhere, versioned like any other code.

A complete theme in one function

library(ggplot2)

theme_rverse <- function(base_size = 12) {
  theme_minimal(base_size = base_size) +
    theme(
      plot.title = element_text(face = "bold", colour = "#1b2a4a",
                                size = rel(1.15)),
      plot.subtitle = element_text(colour = "#5a6478",
                                   margin = margin(b = 10)),
      plot.title.position = "plot",
      axis.title = element_text(colour = "#1b2a4a"),
      panel.grid.minor = element_blank(),
      panel.grid.major = element_line(colour = "#e4e8f0"),
      legend.position = "bottom",
      strip.text = element_text(face = "bold", colour = "#1b2a4a")
    )
}

scale_colour_rverse <- function(...) {
  scale_colour_manual(values = c("#2f6fed", "#17a2b8", "#1b2a4a",
                                 "#e8590c", "#6f42c1"), ...)
}

Before and after

The same plot, the same code — the only difference is the final line.

p <- ggplot(iris, aes(Sepal.Length, Petal.Length, colour = Species)) +
  geom_point(alpha = 0.75) +
  labs(title = "Default ggplot2 look",
       subtitle = "Grey panel, default palette, top-left legend nowhere in particular",
       x = "Sepal length (cm)", y = "Petal length (cm)")
p

Figure 1

p +
  labs(title = "With theme_rverse() and the brand palette",
       subtitle = "One added line — typography, grid and colours now match every other figure") +
  theme_rverse() +
  scale_colour_rverse()

Figure 2

Make it the default

The step most teams skip: you don’t have to add + theme_rverse() to every plot. Set it once at the top of the script or in a package .onLoad():

theme_set(theme_rverse())
options(ggplot2.discrete.colour = scale_colour_rverse)

From that line on, every ggplot in the session is on-brand by default — and when the brand changes, you update one function, re-render, and every figure in every report follows.

Where to keep it

• One project? A R/theme.R file sourced at the top of the analysis.
• A team? An internal R package (yourorg.theme) — install once, library() everywhere. This is exactly the kind of small internal package we build in our package development service.