3 For Intermediate

📊 Interactive Plots in R: plotly and ggplotly

Interactive figures are extremely useful during data exploration and dashboards.

In this section, we introduce two approaches for interactivity:

ggplotly() — convert an existing ggplot2 plot into an interactive widget

plotly — build interactive plots directly using Plotly’s own grammar

3.0.1 ⭐ ggplotly(): Add Interactivity to an Existing ggplot

ggplotly() is a converter.

It takes a normal ggplot2 object and transforms it into an interactive Plotly plot, with zooming, panning, hovering, and tooltips.

✔ When to use ggplotly()

Use it when:

  1. You already have a ggplot and want to enhance it with interactivity.

  2. You want to keep your ggplot aesthetics, including:

facet_wrap

themes (theme_minimal(), theme_pubr(), etc.)

fill, color, and shape aesthetics

scales and labels

  1. You want a quick, simple solution with minimal code changes.

🔧 Example

library(plotly)
p <- ggplot(mpg, aes(displ, hwy, color = class)) +
  geom_point(size = 3) +
  labs(
    title = "Engine Size vs Highway MPG",
    x = "Displacement",
    y = "Highway mileage"
  ) +
  theme_minimal()

ggplotly(p)

✨ Output

Interactive scatter plot

Hover tooltips

Zooming, box selection, and legend toggling

Looks almost identical to your original ggplot

3.0.2 ⭐ Plotly (native): Build Interactive Plots Directly

Plotly also has its own plotting grammar using plot_ly().

This approach offers more control and more interactivity than converting from ggplot.

✔ When to use native plotly

Use it when:

  1. You’re creating dashboards (Shiny, Quarto).

  2. You want advanced interactivity

  3. You need performance with large datasets.

🔧 Example

plot_ly(
  data = mpg,
  x = ~displ,
  y = ~hwy,
  color = ~class,
  type = "scatter",
  mode = "markers"
)

3.0.3 Exercises

Using the built-in mpg dataset:

  1. Make a histogram of hwy (highway fuel efficiency).
  2. Fill the bars by class.
  3. Use 30 bins.
  4. Add a title: “Highway Mileage Distribution”
  5. Apply theme_minimal().
  6. Convert your ggplot object into an interactive figure with ggplotly().

Maybe you can also try facet_wrap(~year). Try to re-plot some plots we’ve learned before.

You can also compare it to native plotly