This is just following up with the example data you sent. This will create a list 'result' that will have the subset of data between the 10% & 90%-tiles of the data:
> #My reproducible example: > firm<-sort(rep(1:1000,10),decreasing=F) > year<-rep(1998:2007,1000) > industry<-rep(c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10),rep(6,10),rep(7,10),rep(8,10),rep(9,10), + rep(10,10)),1000) > X1<-rnorm(10000) > data<-data.frame(firm, industry,year,X1) > # split the data by industry/year > d.s <- split(data, list(data$industry, data$year), drop=TRUE) > result <- lapply(d.s, function(.id){ + # get 10/90% values + .limit <- quantile(.id$X1, prob=c(.1, .9)) + subset(.id, X1 >= .limit[1] & X1 <= .limit[2]) + }) > str(result) List of 100 $ 1.1998 :'data.frame': 800 obs. of 4 variables: ..$ firm : int [1:800] 1 21 31 41 51 61 71 81 91 111 ... ..$ industry: num [1:800] 1 1 1 1 1 1 1 1 1 1 ... ..$ year : int [1:800] 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 ... ..$ X1 : num [1:800] 0.659 -0.105 -0.617 0.342 -1.077 ... $ 2.1998 :'data.frame': 800 obs. of 4 variables: ..$ firm : int [1:800] 2 32 42 52 62 72 102 112 132 162 ... ..$ industry: num [1:800] 2 2 2 2 2 2 2 2 2 2 ... ..$ year : int [1:800] 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 ... ..$ X1 : num [1:800] -1.1044 -0.0666 -0.9184 0.3469 -0.2348 ... You can see that the 'name' of the list element is the industry.year combination; this can also be seen in the data. On Mon, Aug 2, 2010 at 6:20 PM, Cecilia Carmo <cecilia.ca...@ua.pt> wrote: > Thank you for your help but I don't understand how can I have a dataframe > with the columns: firm, year, industry, X1 and X2. Could you help me > (again)? > > > Cecília Carmo > > > Em Sat, 31 Jul 2010 22:10:38 -0400 > jim holtman <jholt...@gmail.com> escreveu: >> >> This will split the data by industry & year and then return the values >> that include the 80%-tile (>=10% & <= 90%) >> >> # split the data by industry/year >> d.s <- split(data, list(data$industry, data$year), drop=TRUE) >> result <- lapply(d.s, function(.id){ >> # get 10/90% values >> .limit <- quantile(.id$X1, prob=c(.1, .9)) >> subset(.id, X1 >= .limit[1] & X1 <= .limit[2]) >> }) >> >> This returns a list of 100 elements for each combination. >> >> On Sat, Jul 31, 2010 at 9:39 PM, Cecilia Carmo <cecilia.ca...@ua.pt> >> wrote: >>> >>> Hi everyone! >>> >>> #I need a loop or a function that creates a X2 variable that is X1 >>> without >>> the extreme values (or X1 winsorized) by industry and year. >>> >>> #My reproducible example: >>> firm<-sort(rep(1:1000,10),decreasing=F) >>> year<-rep(1998:2007,1000) >>> >>> industry<-rep(c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10),rep(6,10),rep(7,10),rep(8,10),rep(9,10), >>> rep(10,10)),1000) >>> X1<-rnorm(10000) >>> data<-data.frame(firm, industry,year,X1) >>> data >>> >>> The way I’m doing this is very hard. I split my sample by industry and >>> year, >>> for each industry and year I calculate the 10% and 90% quantiles, then I >>> create a X2 variable like this: >>> >>> industry1<-subset(data,data$industry==1) >>> >>> ind1year1999<-subset(industry1,industry1$year==1999) >>> q1<-quantile(ind1year1999$X1,probs=0.1,na.rm=TRUE) >>> q99<-quantile(ind1year1999$X1,probs=0.90,na.rm=TRUE) >>> >>> ind1year1999winsorized<-transform(ind1year1999,X2=ifelse(X1<q1,q1,ifelse(X1>q99,q99,X1))) >>> >>> ind1year2000<-subset(industry1,industry1$year==2000) >>> q1<-quantile(ind1year2000$X1,probs=0.1,na.rm=TRUE) >>> q99<-quantile(ind1year2000$X1,probs=0.90,na.rm=TRUE) >>> >>> ind1year2000winsorized<-transform(ind1year2000,X2=ifelse(X1<q1,q1,ifelse(X1>q99,q99,X1))) >>> >>> I repeat this for all years and industries, and then I merge/bind all >>> again >>> to have a new dataframe with all the columns of the dataframe «data» plus >>> X2. >>> >>> Could anyone help me doing this in a easier way? >>> >>> Thanks >>> Cecília Carmo >>> Universidade de Aveiro - Portugal >>> >>> ______________________________________________ >>> 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. >>> >> >> >> >> -- >> Jim Holtman >> Cincinnati, OH >> +1 513 646 9390 >> >> What is the problem that you are trying to solve? > > > -- Jim Holtman Cincinnati, OH +1 513 646 9390 What is the problem that you are trying to solve? ______________________________________________ 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.