Better ask for local help if you can't reduce your code to some minimal
examples so that we can understand easily what you are looking for.
On 02.03.2015 10:38, Rami Alzebdieh wrote:
Dear Sir,
I start using (R) 3 months ago, and I am still learning,
Same for me .... after more than 16 years.
Best,
Uwe Ligges
> I have a project and I am using R in this project, my friend helped
me to build a code for this project and it's working perfect, but I need
to make a small change in, it looks very simple but for me it's very
complicated. I insert the code and I hope if you can help me this
problem. I highlighted what exactly I need to change. This project is
calculating the market and industry weighted returns for each based on
the date levels.
sync = read.csv("country-14.csv",header=T)
id.country = 14
sync = sync[sync$country!="country" & sync$country==id.country,-c(2,5)]
sync$price=as.numeric(as.character(sync$price))
sync$mv=as.numeric(as.character(sync$mv))
attach(sync)
#### Calculate returns and add to the dataset
n.comp = nlevels(as.factor(as.character(sync$company_name)))
comp.names = levels(as.factor(as.character(sync$company_name)))
data = vector("list",n.comp)
for(i in 1:n.comp){
temp = sync[sync$company_name==comp.names[i],]
data[[i]] =
cbind(temp,c(NA,diff(temp$price)/temp$price[1:(length(temp$price)-1)]))
}
sync = do.call(rbind,data)
names(sync)[7] = "returns"
detach(sync)
attach(sync)
#### Fill industry_code column
industry_code=rep(NA,dim(sync)[1])
for(i in 1:dim(sync)[1]){
if(nchar(as.character(company_code[i])) == 3){
industry_code[i] = as.numeric(substr(as.character(company_code[i]),1,1))
} else {
industry_code[i] = as.numeric(substr(as.character(company_code[i]),1,2))
}
print((i/dim(sync)[1])*100)
}
sync = cbind(sync,as.factor(industry_code))
names(sync)[8] = "industry_code"
detach(sync)
attach(sync)
#### Calculate market weighted returns and add to the dataset
market_returns = rep(NA,dim(sync)[1])
industry_returns = rep(NA,dim(sync)[1])
for(i in 1:nlevels(date)){
data = sync[date==levels(date)[i],]
data$company_name = as.factor(as.character(data$company_name))
for(m in 1:nlevels(data$company_name)){
index1 = data$company_name == levels(data$company_name)[m]
index2 = date==levels(date)[i] &
company_name==levels(data$company_name)[m]
market_returns[index2] =
(sum(data$returns*(data$mv/sum(data$mv,na.rm=TRUE)),na.rm=TRUE) -
(data$returns[index1]*(data$mv[index1]/sum(data$mv,na.rm=TRUE))))/(nlevels(data$company_name)-1)
## this what I need to change, instead of using the number of levels companies
in the dataset (nlevels(data$company_name) , I need to put the number of
returns values(data$returns) without NA (by the way this code is calculating
returns at the date level as you can see from above)
}
print(i/nlevels(date))
}
sync = cbind(sync,market_returns)
names(sync)[9] = "market_returns"
detach(sync)
attach(sync)
#### Calculate industry weighted returns and add to the dataset
for(i in 1:nlevels(date)){
for(k in 1:nlevels(as.factor(as.character(industry_code)))){
data1 = sync[date==levels(date)[i] &
industry_code==levels(as.factor(as.character(industry_code)))[k],]
data1$company_name = as.factor(as.character(data1$company_name))
for(l in 1:nlevels(data1$company_name)){
index3 = data1$company_name == levels(data1$company_name)[l]
index4 = date==levels(date)[i] &
company_name==levels(data1$company_name)[l]
industry_returns[index4] =
(sum(data1$returns*(data1$mv/sum(data1$mv,na.rm=TRUE)),na.rm=TRUE) -
(data1$returns[index3]*(data1$mv[index3]/sum(data1$mv,na.rm=TRUE))))/(nlevels(data1$company_name)-1)
## also here I need to change, instead of using the number of levels companies
in the dataset (nlevels(data1$company_name) , I need to put the number of
returns values(data1$returns) without NA (by the way this code is calculating
returns at the date level and industry level as you can see from above)
}
}
print(i/nlevels(date))
}
sync = cbind(sync,industry_returns)
names(sync)[10] = "industry_returns"
detach(sync)
attach(sync)
year = apply(as.matrix(sync$date),1,function(x)
as.factor(substr(as.character(x),7,10)))
sync = cbind(sync,as.factor(year))
names(sync)[11] = "year"
sync = sync[sync$year!="1999",]
sync$year = as.factor(as.character(sync$year))
detach(sync)
attach(sync)
year = as.factor(as.character(year))
industry_code = as.factor(as.character(industry_code))
comp.per.ind = rep(NA, dim(sync)[1])
for(i in 1:nlevels(year)){
for(j in 1:nlevels(industry_code)){
index = year==levels(year)[i] & industry_code==levels(industry_code)[j]
data = sync[index,]
comp.per.ind[index] = nlevels(as.factor(as.character(data$company_name)))
}
}
sync = cbind(sync,as.factor(comp.per.ind))
names(sync)[12] = "comp.per.ind"
detach(sync)
attach(sync)
write.csv(sync,paste("Returns_data",id.country,".csv",sep=""))
Thank you for your help
Rami Alzebdieh
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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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.
