Intro to Animations in ggplot2

How to create animations in ggplot2 with Plotly.

Plotly Studio: Transform any dataset into an interactive data application in minutes with AI. Sign up for early access now.

Frames

Now, along with data and layout, frames is added to the keys that figure allows. Your frames key points to a list of figures, each of which will be cycled through upon instantiation of the plot.

Basic Example

library(plotly)
library(ggplot2)

df <- data.frame(
  x = c(1,2,3,4), 
  y = c(1,2,3,4), 
  f = c(1,2,3,4)
)

p <- ggplot(df, aes(x, y)) +
    geom_point(aes(frame = f))

ggplotly(p)

Mulitple Trace Animations

library(plotly)
library(ggplot2)
library(gapminder)


p <- ggplot(gapminder, aes(gdpPercap, lifeExp, color = continent)) +
  geom_point(aes(size = pop, frame = year, ids = country)) +
  scale_x_log10()

ggplotly(p)

Add Animation Options

To add options to the plot, first convert ggplot2 plot to Plotly variable with ggplotly() and then, add options to that variable.

library(plotly)
library(ggplot2)
library(gapminder)

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, color = continent)) +
  geom_point(aes(size = pop, frame = year, ids = country)) +
  scale_x_log10()

fig <- ggplotly(p)

fig <- fig %>% 
  animation_opts(
    1000, easing = "elastic", redraw = FALSE
  )

fig

Add Button Options

library(plotly)
library(ggplot2)
library(gapminder)

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, color = continent)) +
  geom_point(aes(size = pop, frame = year, ids = country)) +
  scale_x_log10()

fig <- ggplotly(p)

fig <- fig %>% 
  animation_opts(
    1000, easing = "elastic", redraw = FALSE
  )

fig <- fig %>% 
  animation_button(
    x = 1, xanchor = "right", y = 0, yanchor = "bottom"
  )

fig

Add Slider Options

library(plotly)
library(ggplot2)
library(gapminder)

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, color = continent)) +
  geom_point(aes(size = pop, frame = year, ids = country)) +
  scale_x_log10()

fig <- ggplotly(p)

fig <- fig %>% 
  animation_opts(
    1000, easing = "elastic", redraw = FALSE
  )

fig <- fig %>% 
  animation_button(
    x = 1, xanchor = "right", y = 0, yanchor = "bottom"
  )

fig <- fig %>%
  animation_slider(
    currentvalue = list(prefix = "YEAR ", font = list(color="red"))
  )

fig

Create the plot in one function

library(plotly)
library(ggplot2)
library(gapminder)

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, color = continent)) +
  geom_point(aes(size = pop, frame = year, ids = country)) +
  scale_x_log10()

fig <- ggplotly(p) %>% 
  animation_opts(
    1000, easing = "elastic", redraw = FALSE
  ) %>% 
  animation_button(
    x = 1, xanchor = "right", y = 0, yanchor = "bottom"
  ) %>%
  animation_slider(
    currentvalue = list(prefix = "YEAR ", font = list(color="red"))
  )

fig

Reference

To read more on animations see The Plotly Book.

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)