[R] ggplot2: mapping categorical variable to color aesthetic with faceting

[Bryan Hanson]

Hi Baptiste:  Thanks for the suggestion.  It will work perfectly.

I would have never considered assigning a color to a variable that contained
no colors at all!  I guess this is part of the aesthetic concept, which I
haven't had time to reflect on much.  Then later, specify a manual color
scale which then maps back onto the aesthetic.  Clever.

As I stated, I'm just learning ggplot2, and I'm finding the language and
concepts a bit different (I'm not familiar with the "grammar of graphics",
nor am I a computer scientist).  But, I have to say the code I am working up
replaces a much much longer code in base graphics, so I am really liking the
thought put into ggplot2 and the leanness of it - Thanks Hadley!

Thanks again, Bryan


On 10/6/09 12:36 PM, "baptiste auguie" <baptiste.auguie at googlemail.com>
wrote:

> Hi,
> 
> I may be missing an important design decision, but could you not have
> only a single data.frame as an argument of your function? From your
> example, it seems that the colour can be mapped to the fac1 variable
> of "data",
> 
> compareCats <- function(data) {
> 
>    require(ggplot2)
>    p <- ggplot(data, aes(fac1, res, color=fac1)) + facet_grid(. ~ fac2)
>    jit <- position_jitter(width = 0.1)
>    p <- p + layer(geom = "jitter", position = jit) +
>      scale_colour_manual(values=c("red", "blue"))
>    print(p)
>    }
> 
> 
> test <- data.frame(res = rnorm(100), fac1 = as.factor(rep(c("A", "B"), 50)),
>    fac2 = as.factor(rep(c("lrg", "lrg", "sm", "sm"), 25)))
> 
> compareCats(data = test)
> 
> rem <- runif(5, 1, 100) # randomly remove a few points here and there
> last_plot() %+% test[-rem,] # replot with new dataset
> 
> 
> HTH,
> 
> baptiste
> 
> 
> 
> 2009/10/6 Bryan Hanson <hanson at depauw.edu>:
>> Hello Again...  I¹m making a faceted plot of a response on two categorical
>> variables using ggplot2 and having troubles with the coloring. Here is a
>> sample that produces the desired plot:
>> 
>> compareCats <- function(data, res, fac1, fac2, colors) {
>> 
>>    require(ggplot2)
>>    p <- ggplot(data, aes(fac1, res)) + facet_grid(. ~ fac2)
>>    jit <- position_jitter(width = 0.1)
>>    p <- p + layer(geom = "jitter", position = jit, color = colors)
>>    print(p)
>>    }
>> 
>> test <- data.frame(res = rnorm(100), fac1 = as.factor(rep(c("A", "B"), 50)),
>>    fac2 = as.factor(rep(c("lrg", "lrg", "sm", "sm"), 25)))
>> 
>> compareCats(data = test, res = res, fac1 = fac1, fac2 = fac2, colors =
>> c("red", "blue"))
>> 
>> Now, if I get away from idealized data where there are the same number of
>> data points per group (25 in this case), I run into problems.  So, if you
>> do:
>> 
>> rem <- runif(5, 1, 100) # randomly remove a few points here and there
>> test <- test[-rem,]
>> compareCats(data = test, res = res, fac1 = fac1, fac2 = fac2, colors =
>> c("red", "blue"))
>> 
>> R throws an error due to mismatch between the recycling of colors and the
>> actual number of data points:
>> 
>> Error in `[<-.data.frame`(`*tmp*`, gp, value = list(colour = c("red",  :
>>  replacement element 1 has 2 rows, need 47
>> 
>> I'm new to ggplot2, but have been through the book and the web site enough
>> to know that my problem is "mapping the varible to the aesthetic"; I also
>> know I can either "map" or "set" the colors.
>> 
>> The question, finally:  is there an simple/elegant way to map a list of two
>> colors corresponding to A and B onto any random sample size of A and B with
>> faceting?  If not, and I must "set" the colors:  Do I compute the length of
>> all possible combos of A, B with lrg, sm, and then create one long vector of
>> colors for the entire plot?  I tried something like this, and was not
>> successful, but perhaps could be with more work.
>> 
>> All advice appreciated, Bryan (session info below)
>> 
>> *************
>> Bryan Hanson
>> Professor of Chemistry & Biochemistry
>> DePauw University, Greencastle IN USA
>> 
>>> sessionInfo()
>> R version 2.9.2 (2009-08-24)
>> i386-apple-darwin8.11.1
>> 
>> locale:
>> en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>> 
>> attached base packages:
>> [1] grid      datasets  tools     utils     stats     graphics  grDevices
>> methods
>> [9] base
>> 
>> other attached packages:
>>  [1] ggplot2_0.8.3      reshape_0.8.3      proto_0.3-8        mvbutils_22.0
>>  [5] ChemoSpec_1.1      lattice_0.17-25    mvoutlier_1.4      plyr_0.1.8
>>  [9] RColorBrewer_1.0-2 chemometrics_0.4   som_0.3-4
>> robustbase_0.4-5
>> [13] rpart_3.1-45       pls_2.1-0          pcaPP_1.7          mvtnorm_0.9-7
>> [17] nnet_7.2-48        mclust_3.2         MASS_7.2-48        lars_0.9-7
>> [21] e1071_1.5-19       class_7.2-48
>> 
>> ______________________________________________
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>>