In R, I plot with ggplot. Inspired by others who have also made themes that look nicer than the default options provided in the package, I present my own theme (at the end).

# package contains ggplot
library(tidyverse)

Examples of default plots

I’ll plot the built-in mtcars data, with some added titles and with modifications to the points (colors and shapes).

This default plot theme has one glaring issue, in my opinion: the gray background. It reduced contrast and obscures patterns. It can work, but even then it needs an all-gray plot to work, also requiring really dark points to see well. Here are two other default plot themes.

# theme_bw
p + theme_bw()

# theme_classic
p + theme_classic()

The classic choice isn’t bad; has a clean feel that says, “I’m ready for a look”. But making your own theme isn’t that hard, and the results can be more rewarding. Of course, packages like ggthemes and hrbrthemes¹ exist, but again, it isn’t that hard to do yourself.

theme_gradcylinder

library(extrafont)

## Registering fonts with R

rc <- c("Roboto Condensed")

# My own ggplot2 theme
theme_set(
  theme_minimal(base_family = rc,
                base_size = 14) +
    theme(
      plot.background = NULL,
      plot.margin = margin(t = 2, r = 2, b = 2, l = 2, unit = "pt"),
      panel.grid = element_line(color = "#F1F1F1"),
      panel.border = element_blank(),
      axis.line = element_blank(),
      axis.ticks = element_blank(),
      axis.title.y = element_text(
        hjust = 1,
        margin = margin(t = 0, r = 10, b = 0, l = 0, unit = "pt")),
      axis.title.x = element_text(
        hjust = 0,
        margin = margin(t = 10, r = 0, b = 0, l = 0, unit = "pt")),
      axis.text = element_text(family = rc),
      legend.title.align = 0,
      legend.key.height = unit(x = 5, units = "mm"),
      legend.justification = c(1, 1),
      legend.position = c(1, 1)
    )
)

p

I currently like the Roboto Condensed font (used with extrafont). I like using faint lines behind the data, that help interested viewers extract data. I like aligning the axis titles to the top and left. This makes sense as most plots are read left-to-right.