Hmm
>
DF<-data.frame(name=rep(1:5,each=2),x1=rep("A",10),x2=seq(10,19,by=1),x3=rep(NA,10),x4=seq(20,29,by=1))
DF$x3[5]<-50
mask<-apply(sample,2,"%in%", target)
DF
name x1 x2 x3 x4
1 1 A 10 NA 20
2 1 A 11 NA 21
3 2 A 12 NA 22
4 2 A 13 NA 23
5 3 A 14 50 24
6 3 A 15 NA 25
7 4 A 16 NA 26
8 4 A 17 NA 27
9 5 A 18 NA 28
10 5 A 19 NA 29
mask
[,1] [,2] [,3] [,4] [,5]
[1,] FALSE FALSE FALSE FALSE FALSE
[2,] FALSE FALSE FALSE FALSE FALSE
[3,] TRUE TRUE FALSE TRUE FALSE
[4,] FALSE FALSE FALSE FALSE FALSE
[5,] TRUE FALSE FALSE FALSE FALSE
mask<-data.frame(a=TRUE,b=TRUE,!mask)
DF[mask]<-NA
Error in FUN(X[[1L]], ...) :
only defined on a data frame with all numeric variables
DF2<-data.frame(DF[,3:5])
mask<-apply(sample,2,"%in%", target)
mask<-data.frame(!mask)
DF2[mask]<-NA
Error in FUN(X[[1L]], ...) :
only defined on a data frame with all numeric variables
DF2
x2 x3 x4
1 10 NA 20
2 11 NA 21
3 12 NA 22
4 13 NA 23
5 14 50 24
6 15 NA 25
7 16 NA 26
8 17 NA 27
9 18 NA 28
10 19 NA 29
mask<-apply(DF2,2,"%in%", target)
mask<-data.frame(!mask)
DF2[mask]<-NA
Error in FUN(X[[1L]], ...) :
only defined on a data frame with all numeric variables
On Tue, Jun 22, 2010 at 12:23 AM, Petr PIKAL <petr.pi...@precheza.cz> wrote:
> Hi
>
> r-help-boun...@r-project.org napsal dne 22.06.2010 08:28:04:
>
> > The following dataframe will illustrate the problem
> >
> >
>
> DF<-data.frame(name=rep(1:5,each=2),x1=rep("A",10),x2=seq(10,19,by=1),x3=rep
> > (NA,10),x4=seq(20,29,by=1))
> > DF$x3[5]<-50
> >
> > # we have a data frame. we are interested in the columns x2,x3,x4 which
> > contain sparse
> > # values and many NA.
> > DF
> > name x1 x2 x3 x4
> > 1 1 A 10 NA 20
> > 2 1 A 11 NA 21
> > 3 2 A 12 NA 22
> > 4 2 A 13 NA 23
> > 5 3 A 14 50 24
> > 6 3 A 15 NA 25
> > 7 4 A 16 NA 26
> > 8 4 A 17 NA 27
> > 9 5 A 18 NA 28
> > 10 5 A 19 NA 29
> >
> > # we have a list of "target values that we want to search for in the
> data
> > frame
> > # if the value is in the data frame we want to keep it there, otherwise,
> > replace it with NA
> >
> > targets<-c(11,12,13,16,19,50,27,24,22,26)
> > # so we apply a test by column to the last 3 columns using the "in" test
> > # this gives us a mask of whether the data frame 'contains' elements in
> the
> > # target list
> >
> > mask<-apply(DF[,3:5],2, "%in%" ,targets)
> > mask
> >
> > x2 x3 x4
> > [1,] FALSE FALSE FALSE
> > [2,] TRUE FALSE FALSE
> > [3,] TRUE FALSE TRUE
> > [4,] TRUE FALSE FALSE
> > [5,] FALSE TRUE TRUE
> > [6,] FALSE FALSE FALSE
> > [7,] TRUE FALSE TRUE
> > [8,] FALSE FALSE TRUE
> > [9,] FALSE FALSE FALSE
> > [10,] TRUE FALSE FALSE
> >
> > # and so DF[2,3] is equal to 11 and 11 is in the target list, so the
> mask is
> > True
> > # now something like DF<- ifelse(mask==T,DF,NA) is CONCEPTUALLY what I
> want
>
> Data frames are quite clever in preserving their dimensions. I would do
>
> mask=data.frame(a=TRUE, b=TRUE, !mask)
>
> to add column 1 and 2
>
> and
>
> DF[mask]<-NA
>
> Regards
> Petr
>
>
> > to do
> > in the end I'd Like a result that looks like
> >
> > name x1 x2 x3 x4
> > 1 1 A NA NA NA
> > 2 1 A 11 NA NA
> > 3 2 A 12 NA 22
> > 4 2 A 13 NANA
> > 5 3 A NA 50 24
> > 6 3 A NA NA NA
> > 7 4 A 16 NA 26
> > 8 4 A NA NA 27
> > 9 5 A NA NA NA
> > 10 5 A 19 NA NA
> >
> > Ive tried forcing the DF and the mask into vectors so that ifelse()
> would
> > work
> > and have tried "apply" using ifelse.. without much luck. any thoughts?
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org 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]]
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