Try this:
data <- data.frame(x1=rnorm(5),x2=rnorm(5),x3=rnorm(5),x4=rnorm(5))
data <- round(data,digits=3)
#get the total counts
n = prod(dim(data))
#set up a dummy array/matrix
dummy <- rep(F, n/2)
dummy[sample(1:(n/2), n*.2)] <- T
# 5x2 dummy matrix with T and F
matrix(dummy, nc = 2)
#subset the T indices in x3 and x4 and replace with NAs
data[,c("x3", "x4")][matrix(dummy, nc = 2)] <- NA
data
# x1 x2 x3 x4
#1 -1.310 0.659 NA 0.510
#2 -3.003 -0.004 NA NA
#3 0.584 0.310 NA -0.087
#4 1.644 -2.792 -0.390 -0.382
#5 -1.791 0.840 1.137 0.820
Richard
On Fri, Aug 16, 2013 at 2:34 PM, arun <[email protected]> wrote:
> Hi,
> May be this helps:
> #data1 (changed `data` to `data1`)
> set.seed(6245)
> data1 <- data.frame(x1=rnorm(5),x2=rnorm(5),x3=rnorm(5),x4=rnorm(5))
> data1<- round(data1,digits=3)
>
> data2<- data1
>
> data1[,3:4]<-lapply(data1[,3:4],function(x){x1<-
> match(x,sample(unlist(data1[,3:4]),round(0.8*length(unlist(data1[,3:4])))));x[
> is.na(x1)]<-NA;x})
> data1
> # x1 x2 x3 x4
> #1 0.482 1.320 NA -0.142
> #2 -0.753 -0.041 -0.063 0.886
> #3 0.028 -0.256 -0.069 0.354
> #4 -0.086 0.475 0.244 0.781
> #5 0.690 -0.181 1.274 1.633
>
>
> #or
> data2[,3:4]<-lapply(data2[,3:4],function(x){x1<-
> match(x,sample(unlist(data2[,3:4]),round(0.8*length(unlist(data2[,3:4])))));x[
> is.na(x1)]<-NA;x})
> data2
> # x1 x2 x3 x4
> #1 0.482 1.320 -0.859 -0.142
> #2 -0.753 -0.041 NA NA
> #3 0.028 -0.256 -0.069 0.354
> #4 -0.086 0.475 0.244 0.781
> #5 0.690 -0.181 1.274 1.633
> A.K.
>
>
>
> ----- Original Message -----
> From: Christopher Desjardins <[email protected]>
> To: "[email protected]" <[email protected]>
> Cc:
> Sent: Friday, August 16, 2013 3:02 PM
> Subject: [R] Randomly drop a percent of data from a data.frame
>
> Hi,
> I have the following data.
>
> > set.seed(6245)
> > data <- data.frame(x1=rnorm(5),x2=rnorm(5),x3=rnorm(5),x4=rnorm(5))
> > round(data,digits=3)
> x1 x2 x3 x4
> 1 0.482 1.320 -0.859 -0.142
> 2 -0.753 -0.041 -0.063 0.886
> 3 0.028 -0.256 -0.069 0.354
> 4 -0.086 0.475 0.244 0.781
> 5 0.690 -0.181 1.274 1.633
>
> What I would like to do is drop 20% of the data. But I want this 20% to
> only come from dropping data from x3 and x4. It doesn't have to be evenly,
> i.e. I don't care to drop 2 from x3 and 2 from x4 or make sure only one
> observation has missing data on only one variable. I just want to drop 20%
> of the data through x3 and x4 only. In other words,
>
> x1 x2 x3 x4
> 1 0.482 1.320 -0.859 NA
> 2 -0.753 -0.041 -0.063 0.886
> 3 0.028 -0.256 NA 0.354
> 4 -0.086 0.475 NA 0.781
> 5 0.690 -0.181 NA 1.633
>
> OR
>
> x1 x2 x3 x4
> 1 0.482 1.320 NA -0.142
> 2 -0.753 -0.041 -0.063 0.886
> 3 0.028 -0.256 NA NA
> 4 -0.086 0.475 0.244 NA
> 5 0.690 -0.181 1.274 1.633
>
> OR
>
> x1 x2 x3 x4
> 1 0.482 1.320 -0.859 -0.142
> 2 -0.753 -0.041 -0.063 NA
> 3 0.028 -0.256 -0.069 NA
> 4 -0.086 0.475 0.244 NA
> 5 0.690 -0.181 1.274 NA
>
> ETC. are all fine.
>
> Any ideas how I can do this?
> Chris
>
> [[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.
>
>
> ______________________________________________
> [email protected] 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.
>
[[alternative HTML version deleted]]
______________________________________________
[email protected] mailing list
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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.
