In sgplot: Graphic Styles and Colours for Scottish Government Plots

Line charts

Line chart with one line

#| fig.alt = "A line chart using sgplot theme and dark blue colour."

gapminder |>
  filter(country == "United Kingdom") |>
  ggplot(aes(x = year, y = lifeExp)) +
  geom_line(linewidth = 1, colour = sg_colour_values["dark-blue"]) +
  theme_sg() +
  scale_y_continuous(limits = c(0, 82),
                     breaks = seq(0, 80, 20),
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = seq(1952, 2007, 5)) +
  labs(
    x = "Year",
    y = NULL,
    title = "Living Longer",
    subtitle = "Life Expectancy in the United Kingdom 1952-2007",
    caption = "Source: Gapminder"
  )

Line chart with multiple lines

#| fig.alt = "A multiple line chart using sgplot theme and main colour palette."

gapminder |>
  filter(country %in% c("United Kingdom", "China")) |>
  ggplot(aes(x = year, y = lifeExp, colour = country)) +
  geom_line(linewidth = 1) +
  theme_sg(legend = "bottom") +
  scale_colour_discrete_sg() +
  scale_y_continuous(limits = c(0, 82),
                     breaks = seq(0, 80, 20),
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = seq(1952, 2007, 5)) +
  labs(
    x = "Year",
    y = NULL,
    title = "Living Longer",
    subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
    caption = "Source: Gapminder",
    colour = NULL
  )

An example with line labels and no legend can be found in the Adding annotations section.

Bar charts

bar_data <-
  gapminder |>
  filter(year == 2007 & continent == "Europe") |>
  slice_max(order_by = lifeExp, n = 5)

#| fig.alt = "A bar chart using sgplot theme and dark blue colour."

ggplot(bar_data, aes(x = reorder(country, -lifeExp), y = lifeExp)) +
  geom_col(fill = sg_colour_values["dark-blue"]) +
  theme_sg() +
  scale_y_continuous(expand = c(0, 0)) +
  labs(
    x = NULL,
    y = NULL,
    title = "Iceland has the highest life expectancy in Europe",
    subtitle = "Life expectancy in European countries, 2007",
    caption = "Source: Gapminder"
  )

A bar chart can sometimes look better with horizontal bars. This can also be a good option if your bar labels are long and difficult to display horizontally on the x axis. To produce a horizontal bar chart, swap the variables defined for x and y in aes() and make a few tweaks to theme_sg(); draw grid lines for the x axis only by setting the grid argument, and draw an axis line for the y axis only by setting the axis argument.

#| fig.alt = "A horizontal bar chart using sgplot theme and dark blue colour."

ggplot(bar_data, aes(x = lifeExp, y = reorder(country, lifeExp))) +
  geom_col(fill = sg_colour_values["dark-blue"]) +
  theme_sg(grid = "x", axis = "y") +
  scale_x_continuous(expand = c(0, 0)) +
  labs(
    x = NULL,
    y = NULL,
    title = "Iceland has the highest life expectancy in Europe",
    subtitle = "Life expectancy in European countries, 2007",
    caption = "Source: Gapminder"
  )

Grouped bar chart

To create a grouped bar chart, set stat = "identity" and position = "dodge" in the call to geom_bar(). Also assign a variable to fill within aes() to determine what variable is used to create bars within groups. The legend argument in theme_sg() can be used to set the position of the legend.

#| fig.alt = "A grouped bar chart using sgplot theme and colours from main palette"

grouped_bar_data <-
  gapminder |>
  filter(year %in% c(1967, 2007) &
           country %in% c("United Kingdom", "Ireland", "France", "Belgium"))

ggplot(grouped_bar_data,
       aes(x = country, y = lifeExp, fill = as.factor(year))) +
  geom_bar(stat = "identity", position = "dodge") +
  scale_y_continuous(expand = c(0, 0)) +
  theme_sg(legend = "bottom") +
  scale_fill_discrete_sg() +
  labs(
    x = "Country",
    y = NULL,
    fill = NULL,
    title = "Living longer",
    subtitle = "Difference in life expectancy, 1967-2007",
    caption = "Source: Gapminder"
  )

Stacked bar chart

To create a stacked bar chart, set stat = "identity and position = "fill" in the call to geom_bar() and assign a variable to fill as before. This will plot your data as part-to-whole. To plot counts, set position = "identity".

Caution should be taken when producing stacked bar charts. They can quickly become difficult to interpret if plotting non part-to-whole data, and/or if plotting more than two categories per stack. First and last categories in the stack will always be easier to compare across bars than those in the middle. Think carefully about the story you are trying to tell with your chart.

#| fig.alt = "A stacked bar chart using sgplot theme and colours from main palette"

stacked_bar_data <-
  gapminder |>
  filter(year == 2007) |>
  mutate(lifeExpGrouped = cut(lifeExp,
                              breaks = c(0, 75, Inf),
                              labels = c("Under 75", "75+"))) |>
  group_by(continent, lifeExpGrouped) |>
  summarise(n_countries = n(), .groups = "drop")

ggplot(stacked_bar_data,
       aes(x = continent, y = n_countries, fill = lifeExpGrouped)) +
  geom_bar(stat = "identity", position = "fill") +
  theme_sg(legend = "bottom") +
  scale_y_continuous(expand = c(0, 0), labels = scales::percent) +
  coord_cartesian(clip = "off") +
  scale_fill_discrete_sg() +
  labs(
    x = NULL,
    y = NULL,
    fill = "Life Expectancy",
    title = "How life expectancy varies across continents",
    subtitle = "Percentage of countries by life expectancy band, 2007",
    caption = "Source: Gapminder"
  )

Histograms

#| fig.alt = "A histogram with sgplot theme and dark blue colour."

gapminder |>
  filter(year == 2007) |>
  ggplot(aes(x = lifeExp)) +
  geom_histogram(binwidth = 5,
                 colour = "white",
                 fill = sg_colour_values["dark-blue"]) +
  theme_sg() +
  scale_y_continuous(expand = c(0, 0)) +
  labs(
    x = NULL,
    y = "Number of \ncountries",
    title = "How life expectancy varies",
    subtitle = "Distribution of life expectancy, 2007",
    caption = "Source: Gapminder"
  )

Scatterplots

#| fig.alt = "A scatterplot using sgplot theme and dark blue colour."

gapminder |>
  filter(year == 2007) |>
  ggplot(aes(x = gdpPercap, y = lifeExp, size = pop)) +
  geom_point(colour = sg_colour_values["dark-blue"]) +
  theme_sg(axis = "none", grid = "xy") +
  scale_x_continuous(
    labels = function(x) scales::dollar(x, prefix = "£")
  ) +
  scale_size_continuous(labels = scales::comma) +
  labs(
    x = "GDP",
    y = "Life\nExpectancy",
    size = "Population",
    title = stringr::str_wrap(
      "The relationship between GDP and Life Expectancy is complex", 40
    ),
    subtitle = "GDP and Life Expectancy for all countires, 2007",
    caption = "Source: Gapminder"
  )

Small multiples

#| fig.alt = "A small multiples area chart using sgplot theme and main colour palette."

gapminder |>
  filter(continent != "Oceania") |>
  group_by(continent, year) |>
  summarise(pop = sum(as.numeric(pop)), .groups = "drop") |>
  ggplot(aes(x = year, y = pop, fill = continent)) +
  geom_area() +
  theme_sg(axis = "none", ticks = "none", legend = "none") +
  scale_fill_discrete_sg() +
  facet_wrap(~ continent, ncol = 2) +
  scale_y_continuous(breaks = c(0, 2e9, 4e9),
                     labels = c(0, "2bn", "4bn")) +
  coord_cartesian(clip = "off") +
  theme(axis.text.x = element_blank()) +
  labs(
    x = NULL,
    y = NULL,
    title = "Asia's rapid growth",
    subtitle = "Population growth by continent, 1952-2007",
    caption = "Source: Gapminder"
  )

Pie charts

#| fig.alt = "A pie chart using sgplot theme and main palette."

stacked_bar_data |>
  filter(continent == "Europe") |>
  ggplot(aes(x = "", y = n_countries, fill = lifeExpGrouped)) +
  geom_col(colour = "white", position = "fill") +
  coord_polar(theta = "y") +
  theme_sg(grid = "none", axis = "none", ticks = "none") +
  theme(axis.text = element_blank()) +
  scale_fill_discrete_sg() +
  labs(
    x = NULL,
    y = NULL,
    fill = NULL,
    title = "How life expectancy varies in Europe",
    subtitle = "Percentage of countries by life expectancy band, 2007",
    caption = "Source: Gapminder"
  )

Focus charts

#| fig.alt = "A bar chart with the bar for Sweden highlighted in dark blue and other bars in grey."

bar_data |>
  ggplot(
    aes(x = reorder(country, -lifeExp), y = lifeExp,
        fill = country == "Sweden")
  ) +
  geom_col() +
  theme_sg(legend = "none") +
  scale_y_continuous(expand = c(0, 0)) +
  scale_fill_discrete_sg("focus", reverse = TRUE) +
  labs(
    x = NULL,
    y = NULL,
    title = "Sweden has the fourth highest life expectancy in Europe",
    subtitle = "Life expectancy in European countries, 2007",
    caption = "Source: Gapminder"
  )

Interactive charts

To make a ggplot2 chart interactive, use ggplotly() from the plotly package. Note however that ggplotly() has a number of 'quirks', including the following:

• sgplot uses the 'sans' font family, however plotly does not recognise this font. To work around this you should add a further call to theme to set the font family for text to "".

• Subtitles and captions are not supported in ggplotly(). As stated elsewhere in this guidance, titles and subtitles should ideally be included in the body of text surrounding a chart rather than embedded in the chart itself, and so this is hopefully not a big issue. This example therefore has no title, subtitle or caption.

#| fig.alt = "An interactive bar chart using sgplot theme and dark blue colour. A tooltip appears when hovering over each bar."

p <-
  bar_data |>
  # Format text for tooltips
  mutate(tooltip = paste0(
    "Country: ", country, "\n",
    "Life Expectancy: ", round(lifeExp, 1)
  )) |>
  ggplot(aes(x = reorder(country, -lifeExp), y = lifeExp, text = tooltip)) +
  geom_col(fill = sg_colour_values["dark-blue"]) +
  theme_sg(ticks = "x") +
  theme(text = element_text(family = "")) +
  scale_y_continuous(expand = c(0, 0)) +
  labs(
    x = NULL,
    y = NULL
  )

plotly::ggplotly(p, tooltip = "text") |>
  plotly::config(
    modeBarButtons = list(list("resetViews")),
    displaylogo = FALSE
  )

sgplot currently only works with ggplot2 charts, however there are plans to develop the package further to support interactive Highcharts produced using the highcharter package.

sgplot documentation built on June 8, 2025, 12:15 p.m.