Read 2 rows in 1 dataframe for diff - longitudinal data
On Jun 3, 2013, at 9:51 PM, arun wrote:
If it is grouped by "subid" (that would be the difference in the number of changes) subset(ddply(df1,.(subid),mutate,delta=c(FALSE,var[-1]!=var[-length(var)])),delta)[,-4] # subid year var #3 36 2003 3 #7 47 2001 3 #9 47 2005 1 #10 47 2007 3 A.K.
I'm not sure why the first one retruns integer values from the ave() call but the second version works:
df1[ ave( df1$var, df1$subid, FUN=function(x) c( FALSE, x[-1] != x[-length(x)]) ), ]
subid year var 1 36 1999 1 1.1 36 1999 1 1.2 36 1999 1 1.3 36 1999 1 ave( df1$var, df1$subid, FUN=function(x) c( FALSE, x[-1] != x[-length(x)])) [1] 0 0 1 0 0 0 1 0 1 1 Perhaps one of the single item groups sabotaged my simple function.
df1[ as.logical( ave( df1$var, df1$subid, FUN=function(x) c( FALSE, x[-1] != x[-length(x)]) ) ), ]
subid year var 3 36 2003 3 7 47 2001 3 9 47 2005 1 10 47 2007 3
David. > > > ----- Original Message ----- > From: David Winsemius <dwinsemius at comcast.net> > To: arun <smartpink111 at yahoo.com> > Cc: R help <r-help at r-project.org> > Sent: Tuesday, June 4, 2013 12:37 AM > Subject: Re: [R] 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 > David Winsemius Alameda, CA, USA