With base graphics, a histogram of 100 million points

d <- data.frame(x=rnorm(1e8))
system.time(hist(x))

takes just

     user  system elapsed
    0.044   0.004   0.052

which means that the result is ready as my pinkie finger is rising from the ‘Return’ key.

In contrast, if I use ggplot as in

library(ggplot2)
system.time({p<-ggplot(d) + aes(x=x) + geom_histogram();print(p)})

I find I have to wait much longer. The results are

  `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
     user  system elapsed
   43.877  13.766  60.200

so this sub-second task has ballooned to a full minute. Since this is not a large dataset in my line of work, the test shows that my brand-new machine acts more like something from the 1980s.

Don’t get me wrong. I liked the eighties. But I don’t want to go back to 1980s computing power.

And now that I’m revealing myself to be a cranky old fart, I’ll add two more complaints about ggplot defaults:

1. The function ought to choose an appropriate binwidth, instead of saying that it has chosen a poor default.
2. While the ggplot graph looks pretty enough for a magazine, this default low-contrast style can be a problem for some viewers and some printing/reproduction methods.

References and resources

1. Jekyll source code for this blog entry: 2020-09-30-dislike-ggplot.Rmd