[R] loop of quartile groups

[David Winsemius]

On Oct 17, 2012, at 7:23 AM, Charles Determan Jr wrote:

> Greetings R users,
>
> My goal is to generate quartile groups of each variable in my data  
> set.  I
> would like each experiment to have its designated group added as a
> subsequent column.  I can accomplish this individually with the  
> following
> code:
>
> brks <- with(data_variables,
>
>             cut2(var2, g=4))
>
> #I don't want the actual numbers, I need a numbered group
>
> data$test1=factor(brks, labels=1:4)
>
>
> However, I cannot get a loop to work nor can I get a loop to add the
> columns with an appropriate name (ex. quartile_variable).  I have  
> tried
> multiple different ways but can't seem to get it to work.  I think  
> it would
> begin something like this:
>
>
>    for(i in 11:ncol(survival_data_variables)){
>        brks=as.data.frame(with(survival_data_variables,
>            cut2(survival_data_variables[,i], g=4)))
>
>
> Any assistance would be sincerely appreciated.  I would like the  
> final data
> set to have the following layout:
>
>
> ID        var1       var2        var3     var4       quartile var1
> quartile var2        quartile var3      quartile var4
>
>
> Here is a subset of my data to work with:
>
> structure(list(ID = c(11112L, 11811L, 12412L, 12510L, 13111L,
>
> 20209L, 20612L, 20711L, 21510L, 22012L), var1 = c(106, 107,
>
> 116, 67, 76, 146, 89, 62, 65, 116), var2 = c(0, 0, 201,
>
> 558, 526, 555, 576, 0, 531, 649), var3 = c(70.67, 81.33,
>
> 93.67, 84.33, 52, 74, 114, 101, 80.33, 91.33), var4 = c(136,
>
> 139, 142, 138, 140, 140, 136, 139, 140, 139)), .Names = c("ID",
>
> "var1", "var2", "var3", "var4"), row.names = c(NA,
>
> 10L), class = "data.frame")

require(Hmisc)  # which is the package that provides cut2
  dat$quart_var1 <- factor( cut2( dat$var1, g=4), labels=1:4)
  dat
#------------------
       ID var1 var2   var3 var4 quart_var1
1  11112  106    0  70.67  136          3
2  11811  107    0  81.33  139          3
3  12412  116  201  93.67  142          3
4  12510   67  558  84.33  138          1
5  13111   76  526  52.00  140          2
6  20209  146  555  74.00  140          4
7  20612   89  576 114.00  136          2
8  20711   62    0 101.00  139          1
9  21510   65  531  80.33  140          1
10 22012  116  649  91.33  139          3

That won't generalize well, so you could work with this version of the  
same operation:

dat[paste("quart", names(dat)[2], sep="_")] <-  
factor( cut2( dat[[ names(dat)[2] ]], g=4), labels=1:4)

-- 
David Winsemius, MD
Alameda, CA, USA