[R] How to compare stacked histograms/datasets

[Joshua Wiley]

Hi,

Probably easier to work with the raw data, but whatever.  If your data
is in a data frame, dat,

## create row index
dat$x <- 1:21

## load packages
require(ggplot2)
require(reshape2)

## melt the data frame to be long, long dat, ldat for short
ldat <- melt(dat, id.vars="x")

## plot the distributions
ggplot(ldat, aes(x, value, colour = variable)) + geom_line()

## they don't really look on the same scale
## we could scale the data first to have equal mean and variance
dat2 <- as.data.frame(scale(dat))
## remake index so it is not scaled
dat2$x <- 1:21

ldat2 <- melt(dat2, id.vars="x")
ggplot(ldat2, aes(x, value, colour = variable)) + geom_line()

which yields the attached PDF (maybe scrubbed on the official list as
most file extensions are, but should go through to you personally via
gmail).  I'm not sure it's the greatest approach ever, but it gives
you a sense if they go up and down together or at different points.

Cheers,

Josh

On Fri, Jul 6, 2012 at 1:55 PM, Atulkakrana <atulkakrana at gmail.com> wrote:
> Hello All,
>
> I have a couple of stacked histograms which I need to compare/evaluate for
> similarity or difference.
> http://r.789695.n4.nabble.com/file/n4635668/Selection_011.png
>
> I believe rather than evaluating histograms is will be east to work with
> dataset used to plot these stacked histograms, which is in format:
>
> RED                              PURPLE                     BLUE
> GREY                           YELLOW
> 22.0640569395   16.9483985765   0       60.987544484    0
> 8.1850533808    8.8523131673    0       82.962633452    0
> 6.8505338078    6.8950177936    0.756227758     85.4982206406   0.5338078292
> 6.7615658363    5.2491103203    1.6459074733    86.3434163701   0.6672597865
> 5.8274021352    7.384341637     2.1352313167    84.653024911    1.1565836299
> 7.8736654804    6.628113879     1.5569395018    83.9412811388   1.2010676157
> 7.1619217082    8.1850533808    1.2455516014    83.4074733096   1.3790035587
> 5.5604982206    10.2758007117   1.0676156584    83.0960854093   1.0231316726
> 7.1174377224    7.6067615658    0.7117437722    84.5640569395   0.756227758
> 7.8736654804    3.9590747331    0.6672597865    87.5    0.3113879004
> 7.6512455516    7.8736654804    0.5338078292    83.9412811388   0.5338078292
> 7.6067615658    8.9857651246    1.4679715302    81.9395017794   0.3558718861
> 8.9412811388    8.0071174377    1.3790035587    81.6725978648   0.5782918149
> 19.0836298932   9.2081850534    2.1352313167    69.5729537367   1.3790035587
> 14.9911032028   11.0765124555   3.2028469751    70.7295373665   1.0676156584
> 15.3914590747   10.8985765125   3.024911032     70.6850533808   1.2900355872
> 17.4822064057   12.5444839858   2.4911032028    67.4822064057   1.334519573
> 15.8362989324   13.0338078292   2.0017793594    69.128113879    1.334519573
> 17.037366548    10.4537366548   2.4021352313    70.1067615658   1.2010676157
> 20.2846975089   10.0088967972   0       69.706405694    1.0676156584
> 28.7366548043   12.6334519573   0       58.6298932384   0
>
> Is there any possible way I can compare such dataset from multiple
> experiments (n=8) and visually show (plot) that these datasets are in
> consensus or differ from each other?
>
> Awaiting reply,
>
> Atul
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/How-to-compare-stacked-histograms-datasets-tp4635668.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at 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.



-- 
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/
-------------- next part --------------
A non-text attachment was scrubbed...
Name: plots.pdf
Type: application/pdf
Size: 7111 bytes
Desc: not available
URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20120707/888d3a0e/attachment.pdf>