On Fri, 29 Aug 2003, Dowkiw, Arnaud wrote:
> Hi Francisco,
>
> what I would do :
>
> names(X)[c(5,10)]<-c("Age","Gender")
>
> Xnew1<-X[X$Gender==1 & X$Age>=18 & X$Age <=40,]
>
> Xnew2<-X[X$Gender==0 & X$Age>=20 & X$Age <=30,]
>
> Xnew<-rbind(Xnew1,Xnew2)
>
> But there must be something more elegant,
How about
set1 <- with(X, Gender==1 & Age>=18 & Age <=40)
set2 <- with(X, Gender==0 & Age>=20 & Age <=30)
Y <- X[set1 | set 2, ]
> -----Original Message-----
> From: Francisco J. Bido [mailto:[EMAIL PROTECTED]
> Sent: Friday, 29 August 2003 4:10 PM
> To: [EMAIL PROTECTED]
> Subject: [R] Creating a new table from a set of constraints
>
>
> Hi Everyone,
>
> Here's a silly newbie question. How do I remove unwanted rows from an
> R table? Say that I read my data as:
>
> X <- read.table("mydata.txt")
>
> and say that there are columns for age and gender. Call these X[5] and
> X[10], respectively.
> Here, X[5] is a column of positive integers and X[10] is binary valued
> i.e., zero (for male) and one (for female)
>
> Now, say that I want to form a new table called Y which has the
> following constraints:
>
> 1. Only females that are between 18 and 40 years old.
> 2. Only males that are between 20 and 30 years old
>
> I can do this using a typical procedural approach (no different than C
> programmer would) but it seems
> to me that R has many shortcuts and so I thought I ask first before
> heading on an inefficient path. What's
> a good way of doing this, my data set is very large?
>
> Thanks,
> -Francisco
>
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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