#Gganimate without gifski how to
#Gganimate without gifski series

Geom_point(size=2) + transition_reveal(Time) Geom_vline(aes(xintercept = Time)) + transition_reveal(Time)Īnother option is to add a dot instead of a line to the leading edge to indicate the time: >ggplot(df_tidy, aes(x=Time, y=Ratio, color=Cell)) + geom_line() + But first we will beautify the animation by adding a vertical line that runs along: >ggplot(df_tidy, aes(x=Time, y=Ratio, color=Cell)) + geom_line() +

#Gganimate without gifski how to

We will discuss how to save the animation in a bit. Once it’s ready, the animation is shown in the Viewer panel in RStudio. Running this command may take some time (at least a minute on my MacBook). To turn the static plot into an animated plot, we add the function transition_reveal(Time) to reveal the data over time: >ggplot(df_tidy, aes(x=Time, y=Ratio, color=Cell)) + geom_line() + Next, we can read the file, which contains the data in a ‘tidy’ format (to transform your own wide, spreadsheet data into tidy format see this blog) and assign it to the dataframe df_tidy: >df_tidy ggplot(df_tidy, aes(x=Time, y=Ratio, color=Cell)) + geom_line()Īnimated plots can be generated with the gganimate package and we will be using functions from the magick package for saving GIFs and so both are loaded: >require(gganimate) First we load the ggplot2 package that is used for plotting: >require(ggplot2) So I start with a brief explanation of how to generate a plot from time-series data (a more detailed explanation of plotting timeseries data can be found in a previous blog). The basis for the animation is a static plot.

#Gganimate without gifski series

Below, I provide a walk-through for creating an animated time series using R in Rstudio ( footnote 1). That’s where animated plots come in. Animated plots are a great way to display the dynamics of the underlying data.

Ironically, the perception of the dynamics is largely lost in a static plot. Data from time-lapse experiments is often displayed in a graph or plot, to visualize the dynamics of biological systems ( Goedhart, 2020).