Ram H. Sharma
2011-Mar-13 15:49 UTC
[R] replace with quantile value for a large data frame...
Dear R-Experts I am sure this might look simple question for experts, at least is problem for me. I have a large data frame with over 1000 variables and each have different distribution( i.e. have different quantile). I want to create a new grouped data frame, where the new variables where the value falling in first (<25%), second (25% to <50%), third (50% to <75%) and fourth quantiles (>75%) are replaced with 1,2,3, 4 respectively. The following example is just to workout. # my example: X1 <- c(1:10)> X2 <- c(11:20) > X3 <- c(21:30) > X4 <- c(31:40) > X5 <- c(41:50) > dataf <- data.frame(X1, X2, X3, X4, X5) >> # my efforts of the last week led me to this point >for (i along(length(dataf[1,]))) {> qntfun <- function (x) { > XQ <- as.numeric(as.matrix(quantile(x))) > Q1 <- XQ[1] > Q2 <- XQ[2] > Q3 <- XQ[3] > Q4 <- XQ[4] > for (i in 1:length(x)){ > if (x[i] < Q2) { > x[i] <- 1 > } else { > if ( x[i] > Q2 & x[i] < Q3){ > x[i] <- 2 > } else { > if ( x[i] >Q3 & x[i] <Q4) { > x[i] <- 3 > } else { > if (x[i] > Q4) { > x[i] <- 4 > } else{ > x[i] <- 0 > } > } > } > } > } > } > apply(dataf, 1:length(dataf), qntfun) > } ># I got error, I can not fix it. I would be glad to see a more slim solution, but I could not think any. Thanks in advance for your help. Ram Sharma [[alternative HTML version deleted]]
Dimitris Rizopoulos
2011-Mar-13 16:55 UTC
[R] replace with quantile value for a large data frame...
one way is the following:
X1 <- c(1:10)
X2 <- c(11:20)
X3 <- c(21:30)
X4 <- c(31:40)
X5 <- c(41:50)
DF <- data.frame(X1, X2, X3, X4, X5)
as.data.frame(sapply(DF, function (x) {
qx <- quantile(x)
cut(x, qx, include.lowest = TRUE,
labels = 1:4)
}))
You may also have a look at function cut2() from package Hmisc.
I hope it helps.
Best,
Dimitris
On 3/13/2011 4:49 PM, Ram H. Sharma wrote:> Dear R-Experts
>
> I am sure this might look simple question for experts, at least is problem
> for me. I have a large data frame with over 1000 variables and each have
> different distribution( i.e. have different quantile). I want to create a
> new grouped data frame, where the new variables where the value falling in
> first (<25%), second (25% to<50%), third (50% to<75%) and fourth
quantiles
> (>75%) are replaced with 1,2,3, 4 respectively. The following example is
> just to workout.
> # my example:
> X1<- c(1:10)
>
>> X2<- c(11:20)
>> X3<- c(21:30)
>> X4<- c(31:40)
>> X5<- c(41:50)
>> dataf<- data.frame(X1, X2, X3, X4, X5)
>>
>
>
>
>> # my efforts of the last week led me to this point
>>
> for (i along(length(dataf[1,]))) {
>
>> qntfun<- function (x) {
>> XQ<- as.numeric(as.matrix(quantile(x)))
>> Q1<- XQ[1]
>> Q2<- XQ[2]
>> Q3<- XQ[3]
>> Q4<- XQ[4]
>> for (i in 1:length(x)){
>> if (x[i]< Q2) {
>> x[i]<- 1
>> } else {
>> if ( x[i]> Q2& x[i]< Q3){
>> x[i]<- 2
>> } else {
>> if ( x[i]>Q3& x[i]<Q4) {
>> x[i]<- 3
>> } else {
>> if (x[i]> Q4) {
>> x[i]<- 4
>> } else{
>> x[i]<- 0
>> }
>> }
>> }
>> }
>> }
>> }
>> apply(dataf, 1:length(dataf), qntfun)
>> }
>>
> # I got error, I can not fix it. I would be glad to see a more slim
> solution, but I could not think any.
>
> Thanks in advance for your help.
>
> Ram Sharma
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
Web: http://www.erasmusmc.nl/biostatistiek/