loop of quartile groups

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Hello,

There's no function cut2() but it's not very difficult to write one. 
I've named your data example 'dat', it saves keystrokes.
Try the following.

dat <- structure(...etc...)

cut2 <- function(x, g = 0){
     cut(x, breaks = c(-Inf, seq(min(x), max(x), length.out = g)))
}

fun <- function(x) {
     ct <- cut2(x, g = 4)
     factor(ct, levels = levels(ct), labels=1:4)
}

tmp <- sapply(dat[-1], fun)
colnames(tmp) <- paste("quartile", colnames(tmp), sep="_")
dat2 <- cbind(dat, tmp)
str(dat2)

Hope this helps,

Rui Barradas
Em 17-10-2012 15:23, Charles Determan Jr escreveu:
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")

Regards,
Charles

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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