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

[Cecilia Carmo]

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

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--
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?

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and provide commented, minimal, self-contained, reproducible code.