[R] remove extreme values or winsorize – loop - dataframe

[Cecilia Carmo]

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

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