>> That doesn't justify the use of a _histogram_ - and regardless of > > The usage highlights meaningful characteristics of the data. > What better justification for any method of analysis and display is > there?
That you're displaying something that is mathematically well founded and meaningful - but my emphasis there was on histogram. I don't think a histogram makes sense, but there are other ways of displaying the same data that would (e.g. a frequency polygon, or maybe a density plot) >> what distributional display you use, logging the counts imposes some >> pretty heavy restrictions on the shape of the distribution (e.g. that >> it must not drop to zero). > > Does there have to be a recognized statistical distribution to use R? My point is about the display - if your binned counts look like 1, 100, 1000, 100, 0, 0, 10, 1000, 1000, how do you display the log counts? > In my case I am using R for all of the analysis and graphics in a > new book. This means that sometimes I have to deal with data sets > that are more or less a jumble of numbers with patterns in a few > places. For instance, the numeric value of integer constants > appearing as one operand of the binary bitwise-AND operator (see > figure 1224.1 of www.knosof.co.uk/cbook/usefigtab.pdf, raw data > at: www.knosof.co.uk/cbook/bandcons.hist.gz) > > qplot(band, binwidth=8, geom="histogram") + scale_y_log() > does a good job of highlighting the peaks. I couldn't find that figure, but I'd think geom = "freqpoly" would be more appropriate. (I'd also suggest adding a bit more space between the data and the margins in your figures - they overlap in many plots). Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.