Cookbook • afcharts

This cookbook provides examples of the code used to produce various chart types using afcharts. There are also examples to demonstrate how to apply further customisation to afcharts charts.

If there is a chart type or task which you think would be useful to include here, please submit a suggestion.

use_afcharts
The examples in this cookbook use the afcharts theme and colour functions explicitly, however it may be easier to make use of the use_afcharts() function if your charts all require a similar style. More information on use_afcharts can be found on the homepage.

Note on use of titles, subtitles and captions
Titles, subtitles and captions have been embedded in the charts in this cookbook for demonstration purposes. However, for accessibility reasons, it is usually preferable to provide titles in the body of the page rather than embedded within the image of the plot.

The following packages are required to produce the example charts in this cookbook:

library(afcharts)
library(ggplot2)
library(dplyr)
library(ggtext)

# Use gapminder data for cookbook charts
library(gapminder)

Line charts

Line chart with one line

gapminder |>
  filter(country == "United Kingdom") |>
  ggplot(aes(x = year, y = lifeExp)) +
  geom_line(linewidth = 1, colour = af_colour_values["dark-blue"]) +
  theme_af() +
  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"
  )

A line chart using afcharts theme and dark blue colour.

Line chart with multiple lines

gapminder |>
  filter(country %in% c("United Kingdom", "China")) |>
  ggplot(aes(x = year, y = lifeExp, colour = country)) +
  geom_line(linewidth = 1) +
  theme_af(legend = "bottom") +
  scale_colour_discrete_af() +
  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
  )

A multiple line chart using afcharts theme and main colour palette.

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)

ggplot(bar_data, aes(x = reorder(country, -lifeExp), y = lifeExp)) +
  geom_col(fill = af_colour_values["dark-blue"]) +
  theme_af() +
  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 using afcharts theme and dark blue colour.

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_af(); 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.

ggplot(bar_data, aes(x = lifeExp, y = reorder(country, lifeExp))) +
  geom_col(fill = af_colour_values["dark-blue"]) +
  theme_af(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"
  )

A horizontal bar chart using afcharts theme and dark blue colour.

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_af() can be used to set the position of the legend.

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_af(legend = "bottom") +
  scale_fill_discrete_af() +
  labs(
    x = "Country",
    y = NULL,
    fill = NULL,
    title = "Living longer",
    subtitle = "Difference in life expectancy, 1967-2007",
    caption = "Source: Gapminder"
  )

A grouped bar chart using afcharts theme and colours from main palette

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.

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_af(legend = "bottom") +
  scale_y_continuous(expand = c(0, 0), labels = scales::percent) +
  coord_cartesian(clip = "off") +
  scale_fill_discrete_af() +
  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"
  )

A stacked bar chart using afcharts theme and colours from main palette

Histograms

gapminder |>
  filter(year == 2007) |>
  ggplot(aes(x = lifeExp)) +
  geom_histogram(binwidth = 5,
                 colour = "white",
                 fill = af_colour_values["dark-blue"]) +
  theme_af() +
  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"
  )

A histogram with afcharts theme and dark blue colour.

Scatterplots

gapminder |>
  filter(year == 2007) |>
  ggplot(aes(x = gdpPercap, y = lifeExp, size = pop)) +
  geom_point(colour = af_colour_values["dark-blue"]) +
  theme_af(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"
  )

A scatterplot using afcharts theme and dark blue colour.

Small multiples

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_af(axis = "none", ticks = "none", legend = "none") +
  scale_fill_discrete_af() +
  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"
  )

A small multiples area chart using afcharts theme and main colour palette.

Pie charts

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_af(grid = "none", axis = "none", ticks = "none") +
  theme(axis.text = element_blank()) +
  scale_fill_discrete_af() +
  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"
  )

A pie chart using afcharts theme and main palette.

Focus charts

bar_data |>
  ggplot(
    aes(x = reorder(country, -lifeExp), y = lifeExp,
        fill = country == "Sweden")
  ) +
  geom_col() +
  theme_af(legend = "none") +
  scale_y_continuous(expand = c(0, 0)) +
  scale_fill_discrete_af("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"
  )

A bar chart with the bar for Sweden highlighted in dark blue and other bars in grey.

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:

afcharts 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.

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 = af_colour_values["dark-blue"]) +
  theme_af(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
  )

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

Annotations

Labelling your chart is often preferable to using a legend, as often this relies on a user matching the legend to the data using colour alone. The legend can be removed from a chart by setting legend = "none" in theme_af().

The easiest way to add an annotation is to manually define the co-ordinates of the required position.

ann_data <- gapminder |>
  filter(country %in% c("United Kingdom", "China"))

ann_data |>
  ggplot(aes(x = year, y = lifeExp, colour = country)) +
  geom_line(linewidth = 1) +
  theme_af(legend = "none") +
  scale_colour_discrete_af() +
  scale_y_continuous(limits = c(0, 82),
                     breaks = seq(0, 80, 20),
                     expand = c(0, 0)) +
  scale_x_continuous(limits = c(1952, 2017),
                     breaks = seq(1952, 2017, 5)) +
  annotate(geom = "label", x = 2008, y = 73, label = "China",
           colour = af_colour_values[1],
           label.size = NA,
           hjust = 0, vjust = 0.5) +
  annotate(geom = "label", x = 2008, y = 79.4, label = "United Kingdom",
           colour = af_colour_values[2],
           label.size = NA,
           hjust = 0, vjust = 0.5) +
  labs(
    x = "Year",
    y = NULL,
    title = "Living Longer",
    subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
    caption = "Source: Gapminder"
  )

A multiple line chart with colour co-ordinated line labels using afcharts theme and main palette.

However, this makes the code difficult to reuse as values are hard coded and not automatically generated from the data. Automating the position of annotations is possible, but more fiddly.

The following examples use geom_label() to use values from the data to position annotations. geom_label() draws a rectangle behind the text (white by default) and a border the same colour as the text (label_size = NA can be used to remove the border). geom_text() is also an option for annotations, but this does not include a background and so can be harder for text to read if it overlaps with other chart elements. These functions also have nudge arguments that can be used to displace text to improve the positioning.

Note that in the previous examples, annotate() also requires a geom (label or text). These operate in the same way as geom_label() and geom_text(), but as discussed, annotate() is only able to deal with fixed values.

ann_labs <- ann_data |>
  group_by(country) |>
  mutate(min_year = min(year)) |>
  filter(year == max(year)) |>
  ungroup()

ann_data |>
  ggplot(aes(x = year, y = lifeExp, colour = country)) +
  geom_line(linewidth = 1) +
  theme_af(legend = "none") +
  scale_colour_discrete_af() +
  scale_y_continuous(limits = c(0, 82),
                     breaks = seq(0, 80, 20),
                     expand = c(0, 0)) +
  scale_x_continuous(limits = c(1952, 2017),
                     breaks = seq(1952, 2017, 5)) +
  geom_label(data = ann_labs,
             aes(x = year, y = lifeExp, label = country, colour = country),
             hjust = 0,
             vjust = 0.5,
             nudge_x = 0.5,
             label.size = NA) +
  labs(
    x = "Year",
    y = NULL,
    title = "Living Longer",
    subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
    caption = "Source: Gapminder"
  )

A multiple line chart with colour co-ordinated line labels using afcharts theme and main2 palette.

Annotations may also be used to add value labels to a bar chart. Note that geom_text() is used here as a background is not required.

ggplot(bar_data, aes(x = reorder(country, -lifeExp), y = lifeExp)) +
  geom_col(fill = af_colour_values["dark-blue"]) +
  geom_text(aes(label = round(lifeExp, 1)),
            nudge_y = -5, colour = "white") +
  theme_af() +
  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 with white text labels at the end of each bar.

Note: The annotate() function should be used to add annotations with manually defined positioning co-ordinates, whereas geom_label() and geom_text() should be used when using co-ordinates defined in a data frame. Although the reverse may work, text can appear blurry.

Other customisations

theme_af() has arguments to control the legend position and appearance of grid lines, axis lines and axis ticks. More information on accepted values can be found in the help file.

Sorting a bar chart

To control the order of bars in a chart, wrap the variable you want to arrange with reorder() and specify what variable you want to sort by. The following example sorts bars in ascending order of life expectancy. To sort in descending order, you would change this to reorder(country, desc(lifeExp)).

bar_data |>
  ggplot(aes(x = lifeExp, y = reorder(country, lifeExp))) +
  geom_col(fill = af_colour_values["dark-blue"]) +
  theme_af(axis = "y", grid = "x")

A bar chart using afcharts theme and dark blue colour with bars sorted in decreasing order by life expectancy.

Examples in the following sections build on this chart.

Changing chart titles

Chart titles such as the main title, subtitle, caption, axis titles and legend titles, can be controlled using labs(). A title can be removed using NULL.

last_plot() +
  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 with title, subtitle and caption. Axis titles have been removed.

Reducing space between chart and axis

By default, a bar chart will have a gap between the bottom of the bars and the axis. This can be removed as follows:

last_plot() + scale_x_continuous(expand = c(0, 0))

The equivalent adjustment can be made for the y axis using scale_y_continuous.

Changing axis limits, breaks and labels

Axis limits, breaks and labels for continuous variables can be controlled using scale_x/y_continuous(). For discrete variables, labels can be changed using scale_x/y_discrete() or alternatively by recoding the variable in the data before creating a chart.

Limits, breaks and labels can be defined with custom values.

last_plot() +
  scale_x_continuous(expand = c(0, 0),
                     limits = c(0, 85),
                     breaks = seq(0, 80, 20),
                     labels = c(seq(0, 70, 20), "80 years"))

A bar chart with fewer x axis breaks and edited labels.

Note that further calls to scale_x/y_continuous will overwrite previous calls, hence why expand = c(0, 0) has been included again in this example.

Adaptive axis limits and break for scale_x/y_continuous() can be defined using the pretty function. This defines breaks that are equally spaced ‘round’ values which cover the range of the data and limits that are the next ‘round’ value just exceeding the range of the data.

limits_pretty <- function(x, ...) range(pretty(x, ...))

last_plot() +
  scale_x_continuous(expand = expansion(mult = c(0, .1)),
                     breaks = pretty, 
                     limits = limits_pretty)

A bar chart with 'round' breaks and limits using the pretty() function.

Formatting labels

Formatting axis labels or legend labels is easily handled using the scales package. The following example formats y axis labels as percentages, however scales can also handle currency and thousands separators.

stacked_bar_data |>
  ggplot(aes(x = continent, y = n_countries, fill = lifeExpGrouped)) +
  geom_bar(stat = "identity", position = "fill") +
  theme_af(legend = "bottom") +
  scale_y_continuous(expand = c(0, 0), labels = scales::percent) +
  scale_fill_discrete_af() +
  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"
  )

A stacked bar chart with y axis labels formatted as percentages.

Avoiding axis/grid lines being cut off

Axis lines and grid lines can sometimes appear ‘cut off’ if they are drawn at the limits of the chart range. You can see in the example in the previous section that the top grid line is slightly narrower than the adjacent tick mark on the y axis. This is because the y axis limit is 100%. As the grid line is centred at 100%, the top half of the line is ‘cut off’. This can be corrected as follows:

last_plot() + coord_cartesian(clip = "off")

A stacked bar chart with top gridline the same width as adjoining tick mark and other grid lines.

Adding a line

To add a horizontal or vertical line across the whole plot, use geom_hline() or geom_vline(). This can be useful to highlight a threshold or average level.

gapminder |>
  filter(country == "United Kingdom") |>
  ggplot(aes(x = year, y = lifeExp)) +
  geom_line(linewidth = 1, colour = af_colour_values[1]) +
  geom_hline(yintercept = 75, colour = af_colour_values[2],
             linewidth = 1, linetype = "dashed") +
  annotate(geom = "text", x = 2007, y = 70, label = "Age 70") +
  theme_af() +
  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"
  )

A line chart with dashed, orange horizontal line at age 75.

Wrapping text

If text is too long, it may be cut off or distort the dimensions of the chart.

plot <-
  ggplot(bar_data, aes(x = reorder(country, -lifeExp), y = lifeExp)) +
  geom_col(fill = af_colour_values["dark-blue"]) +
  theme_af() +
  scale_y_continuous(expand = c(0, 0)) +
  labs(
    x = NULL,
    subtitle = "Life expectancy in European countries, 2007",
    caption = "Source: Gapminder"
  )

plot +
  labs(
    y = "Percentage of countries",
    title = paste("Iceland has the highest life expectancy in Europe",
                  "followed closely by Switzerland")
  )

A bar chart with end of main title text not visible and long y axis title skewing the dimensions of the chart.

There are two suggested ways to solve this issue; Insert \n within a string to force a line break; Use stringr::str_wrap() to set a maximum character width of the string. See examples of both of these methods as follows:

plot +
  labs(
    y = "Percentage\nof countries",
    title = stringr::str_wrap(
      paste("Iceland has the highest life expectancy in Europe",
            "followed closely by Switzerland"),
      width = 50
    )
  )

A bar chart with main title and y axis title text wrapped onto two lines.

Adjusting theme elements

If you find you need to adjust theme elements for your chart, this can be done using theme(). Note that this should be done after the call to theme_af(), otherwise theme_af() may overwrite the specifications you’ve made.

ggplot(bar_data, aes(x = reorder(country, -lifeExp), y = lifeExp)) +
  geom_col(fill = af_colour_values["dark-blue"]) +
  theme_af(axis = "xy") +
  theme(axis.line = element_line(colour = "black"),
        axis.ticks = element_line(colour = "black")) +
  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 using afcharts theme and dark blue colour, with axis lines and ticks coloured black.

You may also consider using markdown or HTML formatted text within your charts. This can be readily achieved with ggtext::element_markdown(). Please refer to Analysis Function guidance in considering the accessibility of custom formatting, such as when using colours.

ann_data <- gapminder |>
  filter(country %in% c("United Kingdom", "China"))

ann_labs <- ann_data |>
  group_by(country) |>
  mutate(min_year = min(year)) |>
  filter(year == max(year)) |>
  ungroup()

ann_data |>
  ggplot(aes(x = year, y = lifeExp, colour = country)) +
  geom_line(linewidth = 1) +
  theme_af(legend = "none") +
  scale_colour_discrete_af() +
  scale_y_continuous(limits = c(0, 82),
                     breaks = seq(0, 80, 20),
                     expand = c(0, 0)) +
  scale_x_continuous(limits = c(1952, 2017),
                     breaks = seq(1952, 2017, 5)) +
  geom_label(data = ann_labs,
             aes(x = year, y = lifeExp, label = country, colour = country),
             hjust = 0,
             vjust = 0.5,
             nudge_x = 0.5,
             label.size = NA) +
  labs(
    x = "Year",
    y = NULL,
    title = "Living Longer",
    subtitle = "Life Expectancy in the
    <span style='color:darkorange;'>United Kingdom</span> and
    <span style='color:navy;'>China</span> 1952-2007",
    caption = "Source: Gapminder"
  ) +
  theme(plot.subtitle = element_markdown())

A line chart using the afcharts theme with coloured text in the subtitle corresponding to the line colours.

Using different colour palettes

afcharts provides colour palettes as set out by the Government Analysis Function suggested colour palettes. These palettes have been developed to meet the Web Content Accessibility Guidelines 2.1 for graphical objects.

The main palette is the default for discrete colour/fill functions, and the sequential palette for continuous colour/fill functions.

More information on the colours used in afcharts can be found at vignette("colours").

Using afcharts colour palettes

The full list of available palettes can be found by running afcharts::af_colour_palettes.

For example, to use the Analysis Function main2 palette:

gapminder |>
  filter(country %in% c("United Kingdom", "China")) |>
  ggplot(aes(x = year, y = lifeExp, colour = country)) +
  geom_line(linewidth = 1) +
  theme_af(legend = "bottom") +
  scale_colour_discrete_af("main2") +
  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
  )

A multiple line chart using afcharts theme and AF main colour palette.

Using your own colour palette

There may be instances where you’d like to use a colour palette that is not available in afcharts. If so, this should be carefully considered to ensure it meets accessibility requirements. The Government Analysis Function guidance outlines appropriate steps for choosing your own accessible colour palette and should be used.

my_palette <- c("#0F820D", "#000000")

gapminder |>
  filter(country == "United Kingdom") |>
  ggplot(aes(x = year, y = lifeExp)) +
  geom_line(linewidth = 1, colour = my_palette[1]) +
  theme_af() +
  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"
  )

A line chart using afcharts theme and first colour from custom palette.

gapminder |>
  filter(country %in% c("United Kingdom", "China")) |>
  ggplot(aes(x = year, y = lifeExp, colour = country)) +
  geom_line(linewidth = 1) +
  theme_af(legend = "bottom") +
  scale_colour_manual(values = my_palette) +
  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
  )

A multiple line chart using afcharts theme and colours from custom palette.

Adding a new colour palette to afcharts

If you use a different palette regularly and feel it would be useful for this to be added to afcharts, please make a suggestion as per the contributing guidance.

Acknowledgments

The afcharts package is based on the sgplot package, written by Alice Hannah.

This cookbook and the examples it contains have been inspired by the BBC Visual and Data Journalism cookbook for R graphics and their bbplot package.