R help - Aug 2003 - 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

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,

Good luck,

Arnaud


-----Original Message-----
From: Francisco J. Bido [mailto:bido at mac.com]
Sent: Friday, 29 August 2003 4:10 PM
To: r-help at stat.math.ethz.ch
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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********************************DISCLAIMER******************...{{dropped}}

Thanks everyone!  I now see how to handle the situation.  This has to 
be the most responsive mailing list ever...

Best,
-Francisco

On Friday, August 29, 2003, at 01:39 AM, Andrew Hayen wrote:
> Also see this page: http://www.ats.ucla.edu/stat/SPLUS/faq/subset_R.htm
>
> A
>
> -----Original Message-----
> From: Francisco J. Bido [mailto:bido at mac.com]
> Sent: Friday, 29 August 2003 4:10 PM
> To: r-help at stat.math.ethz.ch
> 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
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help

I would use the subset() function.  Assuming the data frame has variable 
names "Gender" and "Age", you could do:

Y1 <- subset(X, Gender == 1 & Age >= 18 & Age <= 40)
Y2 <- subset(X, Gender == 0 & Age >= 20 & Age <= 30)

-roger

Francisco J. Bido wrote:
> 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
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help
>