R help - Sep 2006 - Histogram of data with categorical varialbe

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Alexandre Depire wrote:
> Hello,
> I have the following data:
> Km Sex
> 250 1
> 300 2
> 290 2
> 600 1
> 450 2
> 650 1
> .........
>
> I would like to obtain one histogram where the data (or the part) of each
> sex is visible, it is like cumulative histogram or spinogram.
> To be more comprehensible, i would like to know if the following graph is
> obtainable easily in R. It is the first graph on page 5 in the following
> document http://jasp.ism.ac.jp/~nakanoj/workshop04/TalkII.pdf
>   
Something like :

d <- data.frame( x = rnorm(100), sex = sample(c(1,2), replace=TRUE, 
size=100))
out <- hist(d$x, col="gray")
hist(d$x[d$sex==2], col="red", add=T, breaks=out$breaks)
legend("topleft", c("male","female") ,
fill=c("gray","red"))
box()


Cheers,

Romain

-- 
*mangosolutions*
/data analysis that delivers/

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Fax   +44 1249 467 468

On Fri, 15 Sep 2006 16:45:31 +0200 Alexandre Depire wrote:
> Hello,
> I have the following data:
> Km Sex
> 250 1
> 300 2
> 290 2
> 600 1
> 450 2
> 650 1
> .........
> 
> I would like to obtain one histogram where the data (or the part) of
> each sex is visible, it is like cumulative histogram or spinogram.
> To be more comprehensible, i would like to know if the following
> graph is obtainable easily in R. It is the first graph on page 5 in
> the following document
> http://jasp.ism.ac.jp/~nakanoj/workshop04/TalkII.pdf
I think it's not available out of the box, but you can easily generate
this yourself. Using the space shuttle o-ring data as an example (see
also ?spineplot):

  fail <- factor(c(2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1,
    1, 2, 1, 1, 1, 1, 1), levels = c(1, 2), labels = c("no",
"yes"))
  temperature <- c(53, 57, 58, 63, 66, 67, 67, 67, 68, 69, 70, 70,
    70, 70, 72, 73, 75, 75, 76, 76, 78, 79, 81)

The you can do the following:

  ## generate unconditional histogram of numeric variable P(x)
  col <- gray.colors(2)
  ht <- hist(temperature, freq = FALSE, col = col[2])
  ## using the same breaks, compute the conditional histogram P(x|group)
  br <- ht$breaks
  ht2 <- hist(temperature[fail == "yes"], plot = FALSE, freq =
FALSE,
    breaks = br)
  ## and then add the rectangles using the joint densities
  ## P(x & group) = P(x|group) * P(group)
  rect(br[-length(br)], 0, br[-1], ht2$density * mean(fail == "yes"),
    col = col[1])

Furthermore, you can take a look at the "iplots" package which should
provide an interactive approach to this.
Z
 
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