Themes, Annotations and Interactivity

September 10, 2026

Line Chart from Last Class

Add a Theme

Code

dem_waves_chart + theme_minimal()

Can Also Set Theme

If you like particular theme and want to use it for all of your visualizations, use theme_set() in a code chunk at the top of your document, e.g….

```{r}
#| label: my_setup_chunk

theme_set(theme_minimal())
```

… and R will apply that theme to all of the visualizations in your document.

Your Turn!

Produce this scatter plot… Then try different themes.

Add an Annotation

First step, add a horizontal line using geom_hline()…

Code

flfp_line + 
  geom_hline(yintercept = 52, linetype = "dashed", color = "red", linewidth = 1)

Second step, the annotation with annotate()…

Code

flfp_line + 
  geom_hline(yintercept = 52, linetype = "dashed", color = "red", linewidth = 1) +
  annotate("text", x = 1995, y = 55, label = "Global average")

Vertical Reference Line

First step, add a horizontal line using geom_hline()…

Code

flfp_line + 
  geom_vline(xintercept=2020, linetype = "dashed", linewidth = 1)

Second step, add the annotation with annotate()

Code

flfp_line + 
  geom_vline(xintercept=2020, linetype = "dashed", linewidth = 1) +
  annotate("text", x = 2017, y = 35, label = "Pandemic")

Your Turn!

Go to module 2.2
Copy the code you need to make the line chart
Create a horizontal reference line and annotate it
In a new code chunk, create a vertical line and annotate it
Play with the parameters to move and style your line
Try different text, etc.

Interactivity

Any ggplot can become an interactive chart with one function: ggplotly() from the plotly package.

library(plotly)

ggplotly(wealth_flfp_plotly)

Controlling the Tooltip

By default plotly shows every mapped variable. Use tooltip = to pick which ones, and add aes(label = ) for a variable that is not already in the plot…

wealth_flfp_plotly <- wealth_flfp_plotly + aes(label = country) # so plotly keeps country

ggplotly(wealth_flfp_plotly, tooltip = c("country", "gdp_pc", "flfp"))

Your Turn!

Go to module 2.2 and create the basic wealth vs. flfp scatter plot
Now “plotlify” it by wrapping it in ggplotly()
Hover over the points to see the default tooltip
Now use tooltip = to choose which variables appear
Try adding aes(label = country) so you can show the country name

Animated Plots

Two additions: transition_states() picks the variable to animate over, and {closest_state} puts it in the title.

library(gganimate)

flfp_gdp_ts <- wb_data(indicators, mrv = 25) |> # 25 most recent years
    left_join(select(wb_countries(), c(iso3c, region)), by = "iso3c") |>
    drop_na() |> rename(year = date)

ggplot(flfp_gdp_ts, aes(x = gdp_pc, y = flfp)) +
  geom_point(aes(color = region)) +
  scale_x_log10(labels = scales::label_dollar()) +
  scale_y_continuous(labels = scales::label_percent(scale = 1)) +
  transition_states(year) +
  labs(title = "Wealth and female labor force participation, {closest_state}") +
  scale_color_viridis_d(option = "plasma", end = .7)

Your Turn!

Try making an animated scatter plot with different a different y-axis variable
See if you can make the title change based on the year displayed