Read 2 rows in 1 dataframe for diff - longitudinal data
On Jun 3, 2013, at 7:10 PM, arun wrote:
Hi, May be this helps: res1<-df1[with(df1,unlist(tapply(var,list(subid),FUN=function(x) c(FALSE,diff(x)!=0)),use.names=FALSE)),] res1 # subid year var #3 36 2003 3 #7 47 2001 3 #9 47 2005 1 #10 47 2007 3 #or library(plyr) subset(ddply(df1,.(subid),mutate,delta=c(FALSE,diff(var)!=0)),delta)[,-4] # subid year var #3 36 2003 3 #7 47 2001 3 #9 47 2005 1 #10 47 2007 3 A.K.
It's pretty simple with logical indexing:
df1[ c(FALSE, df1$var[-1]!=df1$var[-length(df1$var)]), ]
subid year var 3 36 2003 3 6 47 1999 1 7 47 2001 3 9 47 2005 1 10 47 2007 3 When I count the number of changes in value of var is give me 5. Not sure why you are both leaving out row 6.
David. > > > I need to output a dataframe whenever var changes a value. > > df1 <- data.frame(subid=rep(c(36,47),each=5),year=rep(seq(1999,2007,2),2),var=c(1,1,3,3,3,1,3,3,1,3)) > subid year var > 1 36 1999 1 > 2 36 2001 1 > 3 36 2003 3 > 4 36 2005 3 > 5 36 2007 3 > 6 47 1999 1 > 7 47 2001 3 > 8 47 2003 3 > 9 47 2005 1 > 10 47 2007 3 >> > > I need: > 36 2003 3 > 47 2001 3 > 47 2005 1 > 47 2007 3 > > I am trying to use ddply over subid and use the diff function, but it is not working quiet right. > >> dd <- ddply(df1,.(subid),summarize,delta=diff(var) != 0) >> dd > subid delta > 1 36 FALSE > 2 36 TRUE > 3 36 FALSE > 4 36 FALSE > 5 47 TRUE > 6 47 FALSE > 7 47 TRUE > 8 47 TRUE > > I would appreciate any help on this. > Thank You! > -ST > > ______________________________________________ > R-help at 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. David Winsemius Alameda, CA, USA