Is there any other way to implement R's cumulative animation?

Plotly R, MATLAB, Julia, Net Plotly R
2

I’m currently facing the same issue. The approach described here is not applicable for a few thousand rows of data.

I don’t have a fully working solution, but my idea was to adapt the x-axis range based on the slider value instead of re-using the data for each frame:

library(plotly)

DF <- data.frame(
  x = seq(0, 12, length=50),
  y = runif(n = 50, min = 0, max = 10)
)

steps <- list()
for(i in 1:13){
  steps[[i]] <- list(args = list("xaxis", list(range = c(0, i))), 
                     label = i, 
                     method = "relayout", 
                     value = i
  )
}

# use animation_slider() / animation_button() / filter?
p <- plot_ly(DF, x = ~x, y = ~y, type = "scatter", mode = "lines") %>%
  layout(title = "Cumulative Animations in R without data redundancy",
         xaxis = list(range = steps[[1]]$args[[2]]$range),
         sliders = list(
           list(
             active = 0, 
             currentvalue = list(prefix = "X-max: "), 
             pad = list(t = 60), 
             steps = steps))) 
p

This unfortunately doesn’t provide us with the “Play”-button. But I thought it might be possible
to use animation_slider() / animation_button() in a similar way?

Here is another interesting approach for the python api using filter.