[R] Function to assign quantiles?
hadley wickham
h.wickham at gmail.com
Fri Feb 16 07:51:49 CET 2007
On 2/16/07, Frank E Harrell Jr <f.harrell at vanderbilt.edu> wrote:
> Marc Schwartz wrote:
> > On Thu, 2007-02-15 at 17:50 -0500, Talbot Katz wrote:
> >> Hi.
> >>
> >> If I call the quantiles function as follows:
> >>
> >> qvec = quantiles(dvals,probs=seq(0,1,0.1))
> >>
> >> the results will return a vector something like the following example:
> >>
> >> 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
> >> 100%
> >> 56.0 137.3 238.4 317.9 495.8 568.5 807.4 1207.7 1713.0
> >> 2951.1 8703.0
> >>
> >> Now I want to assign the deciles, 1 - 10, to each observation, so, in the
> >> above example, if dvals[322] = 256, I want to assign qvals[322] = 3, and if
> >> dvals[7216] = 1083, I want qvals[7216] = 7, etc. I would think there would
> >> be a function, or some very quick code to do that, but I couldn't find it.
> >>
> >> Here's what I have now. It works, but I figure there must be a better way:
> >>
> >> asdc <- function(q){max(1,which(qvec<q))}
> >> qvals = apply(matrix(dvals,nrow=1),2,asdc)
> >>
> >>
> >> Any suggestions? Thanks!
> >
> > Take a look at ?cut and use the output of quantile() to define the
> > 'breaks' argument:
> >
> > x <- rnorm(100)
> >
> >> cut(x, breaks = quantile(x, probs = seq(0, 1, 0.1)),
> > include.lowest = TRUE, labels = 1:10)
> > [1] 2 1 9 10 9 3 1 7 5 2 4 1 10 8 4 10 9 9 5 3 5 8
> > [23] 6 9 7 1 10 1 10 9 3 3 9 3 5 5 6 4 8 10 6 2 2 8
> > [45] 6 3 6 9 1 4 7 10 8 7 5 3 1 10 2 1 7 8 8 2 8 8
> > [67] 3 10 4 6 5 1 4 6 4 4 5 9 9 7 2 8 2 5 1 3 7 6
> > [89] 4 6 4 6 2 7 2 10 7 3 5 7
> > Levels: 1 2 3 4 5 6 7 8 9 10
> >
> >
> > HTH,
> >
> > Marc Schwartz
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch 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.
>
> Or see the cut2 function in the Hmisc package
Or the chop function in ggplot package - it's a common problem.
Hadley
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