[R] R Newbie, please help!
jwiley.psych at gmail.com
Fri Jun 4 06:18:22 CEST 2010
test <- data.frame(totret=rnorm(10^7)) #create some sample data
test[-1,"dailyreturn"] <- test[-1,"totret"]/test[-nrow(test),"totret"]
The general idea is to take the column "totret" excluding the first 1,
dividided by "totret" exluding the last row. This gives in effect t+1
(since t is now shorter)/t
I assigned the result to a new column "dailyreturn". For 10^7 rows,
it tooks 1.92 seconds on my system.
On Thu, Jun 3, 2010 at 8:04 PM, Jeff08 <jefferyding at gmail.com> wrote:
> Hello Everyone,
> I just started a new job & it requires heavy use of R to analyze datasets.
> I have a data.table that looks like this. It is sorted by ID & Date, there
> are about 150 different IDs & the dataset spans 3 million rows. The main
> columns of concern are ID, date, and totret. What I need to do is to derive
> daily returns for each ID from totret, which is simply totret at time t+1
> divided by totret at time t.
> X id ticker date_ adjClose totret RankStk
> 427225 427225 00174410 AHS 2001-11-13 21.66 100.00000 1235
> 441910 441910 00174410 AHS 2001-11-14 21.60 99.72300 1235
> 458458 458458 00174410 AHS 2001-11-15 21.65 99.95380 1235
> 284003 284003 00174410 AHS 2001-11-16 21.59 99.67680 1235
> Two problems for me:
> 1)I can't just apply it to the entire column since there will be problems at
> the boundary points where the ID changes from 1 to another. I need to find
> out how to specify a restriction on the name of the ID
> 2) From Java, instinctively I would use a loop to calculate daily returns,
> but I found out that R is very slow with loops, so I need to find an
> efficient way to calculate daily returns with such a huge dataset.
> Thanks a lot!
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> and provide commented, minimal, self-contained, reproducible code.
Senior in Psychology
University of California, Riverside
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