Question

I often visualize one time series against another using scatterplots in Excel, but since recent data are more relavant, I use different highlights for more recent time periods:

In this case the month, week and today plots are simply different (more recent) slices of the same time series, so basically there are four superimposed plots in this chart. How can I do the same in R? I have gotten so far:

But i’d like to replicate what I have in excel. How do I add new plots to the same chart in R?

Or perhaps I could even go further and use the col attribute in the R plot to get a continuous increase in the colour up to the today value, thus avoiding these discreet steps? How would I do that?

Answer 1

Here is a skeleton example of how to go about doing it using ggplot:

library(ggplot2)

day <- 1:100
dat <- data.frame(
  day=day,
  x = day+(1+rnorm(100, 0, 10)),
  y = 5 + day+(1+rnorm(100, 0, 10)),
  when = cut(day, 5)
)

ggplot(dat, aes(x=x, y=y, colour=when)) + geom_point()

And for smooth colours:

ggplot(dat, aes(x=x, y=y, colour=day)) + geom_point() + 
    scale_colour_gradient(low="pink", high="red")