[R] problem of data manipulation
William Dunlap
wdunlap at tibco.com
Mon Jan 18 21:37:18 CET 2010
> -----Original Message-----
> From: Bert Gunter [mailto:gunter.berton at gene.com]
> Sent: Monday, January 18, 2010 12:32 PM
> To: William Dunlap; 'rusers.sh'; r-help at r-project.org
> Subject: RE: [R] problem of data manipulation
>
> Absolutely... so long as you assume the dates are in order --
> or at least
> that the earliest date of a group appears first.
>
> -- Bert
>
Yes, I forgot to mention that requirement. When
there are a lot of small groups run-based methods
(sort then deal with a run at a time) can save a
lot of time. They may also make the intent of
the code more clear, but not everyone sees it that way.
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-bounces at r-project.org
> [mailto:r-help-bounces at r-project.org] On
> Behalf Of William Dunlap
> Sent: Monday, January 18, 2010 12:15 PM
> To: Bert Gunter; rusers.sh; r-help at r-project.org
> Subject: Re: [R] problem of data manipulation
>
> > -----Original Message-----
> > From: r-help-bounces at r-project.org
> > [mailto:r-help-bounces at r-project.org] On Behalf Of Bert Gunter
> > Sent: Monday, January 18, 2010 11:54 AM
> > To: 'rusers.sh'; r-help at r-project.org
> > Subject: Re: [R] problem of data manipulation
> >
> > One way to do it:
> >
> > 1. Convert your date column to the Date class using the
> > as.Date() function.
> > This allows you to do the necessary arithmetic on the dates below.
> > dt <- as.Date(a[,4],"%d/%m/%Y")
> >
> > 2. Create a factor out of your first three columns whose
> > levels are in the
> > same order as the unique rows. Something likes the following
> > should do it:
> > fac <- do.call(paste,a[,-4])
> > fac <- factor(fac, levels=unique(fac))
> >
> > This allows you to choose the groups of rows whose dates you
> > wish to compare
> > and maintain their correct order in the data frame
> >
> > 3. Then use tapply:
> > a[unlist(tapply(dt,fac,function(x)x-min(x) < 7)),]
>
> You can do this without unpacking and repacking
> the data.frame (with tapply) based on the following
> sort of calculation:
>
> > isFirstInRun <- function(x)c(TRUE, x[-1] != x[-length(x)])
> > f <- with(a, isFirstInRun(var1) | isFirstInRun(var2) |
> isFirstInRun(var3))
> > firstRowInRun <- which(f)
> > runNumber <- cumsum(f)
> > dt <- as.Date(a$var4, "%d/%m/%Y")
> > DaysSinceStartOfRun <- dt - dt[firstRowInRun[runNumber]]
> > DaysSinceStartOfRun
> Time differences in days
> [1] 0 0 3 0 4 12
> > a[ DaysSinceStartOfRun < 7, ]
> var1 var2 var3 var4
> 1 s 1 2 01/01/1999
> 2 c 1 2 10/02/2000
> 3 c 1 2 13/02/2000
> 4 n 2 1 11/02/2000
> 5 n 2 1 15/02/2000
>
> Is that what you wanted?
>
> Bill Dunlap
> Spotfire, TIBCO Software
> wdunlap tibco.com
> >
> > (unlist is needed to remove the list structure and
> > concatenate the logical
> > indices to obtain the subscripting vector).
> >
> > Bert Gunter
> > Genentech Nonclinical Statistics
> >
> > -----Original Message-----
> > From: r-help-bounces at r-project.org
> > [mailto:r-help-bounces at r-project.org] On
> > Behalf Of rusers.sh
> > Sent: Monday, January 18, 2010 10:40 AM
> > To: r-help at r-project.org
> > Subject: [R] problem of data manipulation
> >
> > Hello,
> > See my problem below.
> > a<-data.frame(c("s","c","c","n","n","n"),c(rep(1,3),rep(2,3)),
> > c(rep(2,3),rep
> > (1,3)),c("01/01/1999","10/02/2000","13/02/2000","11/02/2000","
> > 15/02/2000","2
> > 3/02/2000"))
> > colnames(a)<-c("var1","var2","var3","var4")
> > > a
> > var1 var2 var3 var4
> > 1 s 1 2 01/01/1999
> > 2 c 1 2 10/02/2000
> > 3 c 1 2 13/02/2000
> > 4 n 2 1 11/02/2000
> > 5 n 2 1 15/02/2000
> > 6 n 2 1 23/02/2000
> >
> > I want to select the observations whose difference of
> > "var4" is less than
> > 7 for the cases with the same values of var1,var2 andvar3.
> > The obervations have the same var1, var2 and var3 are,
> > part1 (obs2 and
> > obs3) and part2 (obs4,obs5, and obs6).
> > For obs2 and obs3, their date difference is less than 7, so
> > we donot need
> > to delete any of them.
> > For obs4,obs5, and obs6,we can see that obs6 should be
> > deleted becuase its
> > date is over 7 dyas longer than obs4.
> > So the final dataset should obs1,obs2,obs3,obs4, and obs5.
> > I have a lot of observations in my dataset, so i hope to do this
> > automatically. Any ideas on this?
> > Thanks.
> > --
> > -----------------
> > Jane Chang
> > Queen's
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
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> > and provide commented, minimal, self-contained, reproducible code.
> >
> > ______________________________________________
> > 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.
> >
>
> ______________________________________________
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> PLEASE do read the posting guide
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>
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