Tech news 6: Creating animated figures

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Published

19/12/2023

This week, some fun with animated figures. We send each other gifs but they rarely come to mind when it comes to showing scientific processes or results. They are actually pretty easy to make in R!

Here are a few examples using gganimate. There are other packages out there but gganimate is really well integrated with ggplot2.

A simple boxplot

library(ggplot2)
library(gganimate)

ggplot(mtcars, aes(factor(cyl), mpg)) + 
  geom_boxplot() + 
  # Here comes the gganimate code
  transition_states(
    gear,
    transition_length = 2,
    state_length = 1
  ) +
  enter_fade() + 
  exit_shrink() +
  ease_aes('sine-in-out’)

Animated boxplot of miles per gallon by number of cylinders from the mtcars dataset, transitioning across gear values

Code and figure by gganimate authors Thomas Lin Pedersen and David Robinson ¹

A much more informative scatter plot with evolution in time

library(gapminder)

ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~continent) +
  # Here comes the gganimate specific bits
  labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year) +
  ease_aes('linear')

Animated scatter plot of GDP per capita versus life expectancy by continent from 1952 to 2007, bubble size proportional to population, created with gganimate and gapminder data

Code and figure by gganimate authors Thomas Lin Pedersen and David Robinson ²

And a map!

library(ggplot2)

center_lat <- 37.8 # Some random data
center_long <- -122.4
width <- 0.2
num_points <- 500
test_data <- data.frame('lat'=rnorm(num_points, mean=center_lat, sd=width),
                        'long'=rnorm(num_points, mean=center_long, sd=width),
                        'year'=floor(runif(num_points, min=1990, max=2020)),
                        'temp'=runif(num_points, min=-10, max=40)
)
min_long <- min(test_data$long)
max_long <- max(test_data$long)
min_lat <- min(test_data$lat)
max_lat <- max(test_data$lat)
num_years <- max(test_data$year) - min(test_data$year) + 1

county_info <- map_data("county", region = "california") # The map background

map_with_shadow <- ggplot(data = county_info,
                          mapping = aes(x = long, y = lat, group = group)) +
   geom_polygon(color = "black", fill = "white") +
   coord_quickmap() +
   theme_void()  +
   geom_point(data = test_data, aes(x = long, y = lat,
                                    color = temp, size = temp, group = year)) +
   coord_quickmap(xlim = c(min_long, max_long), 
                  ylim = c(min_lat, max_lat)) +
   gganimate::transition_time(year) +
   ggtitle('Year: {frame_time}',
           subtitle = 'Frame {frame} of {nframes}') +
   gganimate::shadow_mark()
gganimate::animate(map_with_shadow, nframes = num_years, fps = 2)

Animated map of California counties showing simulated data points coloured by temperature, transitioning year by year from 1990 to 2019

Code and figure by David J. Lilja ³

Great resources

https://rquer.netlify.app/animated_chart/evolution/ many examples but it’s in Spanish
https://rquer.netlify.app/animated_map/animated_map/ especially for maps

Cheers,

Alban

Footnotes

Pedersen T, Robinson D (2022). gganimate: A Grammar of Animated Graphics. https://gganimate.com, https://github.com/thomasp85/gganimate.↩︎
Pedersen T, Robinson D (2022). gganimate: A Grammar of Animated Graphics. https://gganimate.com, https://github.com/thomasp85/gganimate.↩︎
David J. Lilja, “How to Plot and Animate Data on Maps Using the R Programming Language,” University of Minnesota Digital Conservancy, https://hdl.handle.net/11299/220339, June, 2021.↩︎