R help - Jul 2005 - elegant solution to transform vector into percentages?

Hi,

I am looking for an elegant way to transform a vector into percentages of values
that meet certain criteria.

store<-c(1,1.4,3,1.1,0.3,0.6,4,5)

# now I want to get the precentages of values
# that fall into the categories <=M , >M & <=N , >N
# let
M <-.8
N <- 1.2
# In my real example I have many more of these cutoff-points

# What I did is:

out <- matrix(NA,1,3)

  out[1,1] <- ( (sum(store<=M                ))  /length(store) )*100
  out[1,2] <- ( (sum(store> M  & store<= N   ))  /length(store)
)*100
  out[1,3] <- ( (sum(store> N                ))  /length(store) )*100

colnames(out)<-c("percent<=M","percent>M &
<=N","percent>N")
out

But this gets very tedious if I have many cutoff-points. Does anybody know a
more elegant way to do this task?

Thanks so much.

Cheers,
Jens

hist() or cut() followed by tabulate() would probably be the ingredients
you'd want.

Reid Huntsinger

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
jhainm at fas.harvard.edu
Sent: Tuesday, July 26, 2005 3:49 PM
To: r-help at stat.math.ethz.ch
Subject: [R] elegant solution to transform vector into percentages?


Hi,

I am looking for an elegant way to transform a vector into percentages of
values
that meet certain criteria.

store<-c(1,1.4,3,1.1,0.3,0.6,4,5)

# now I want to get the precentages of values
# that fall into the categories <=M , >M & <=N , >N
# let
M <-.8
N <- 1.2
# In my real example I have many more of these cutoff-points

# What I did is:

out <- matrix(NA,1,3)

  out[1,1] <- ( (sum(store<=M                ))  /length(store) )*100
  out[1,2] <- ( (sum(store> M  & store<= N   ))  /length(store)
)*100
  out[1,3] <- ( (sum(store> N                ))  /length(store) )*100

colnames(out)<-c("percent<=M","percent>M &
<=N","percent>N")
out

But this gets very tedious if I have many cutoff-points. Does anybody know a
more elegant way to do this task?

Thanks so much.

Cheers,
Jens

______________________________________________
R-help at stat.math.ethz.ch mailing list
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PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html

use 'cut':
> store<-c(1,1.4,3,1.1,0.3,0.6,4,5)
> x.1 <- cut(store, breaks=c(-Inf,.8,1.2,Inf))
> table(x.1)/length(x.1)*100
x.1
(-Inf,0.8]  (0.8,1.2]  (1.2,Inf] 
        25         25         50 
> 
On 7/26/05, jhainm at fas.harvard.edu <jhainm at fas.harvard.edu>
wrote:
> Hi,
> 
> I am looking for an elegant way to transform a vector into percentages of
values
> that meet certain criteria.
> 
> store<-c(1,1.4,3,1.1,0.3,0.6,4,5)
> 
> # now I want to get the precentages of values
> # that fall into the categories <=M , >M & <=N , >N
> # let
> M <-.8
> N <- 1.2
> # In my real example I have many more of these cutoff-points
> 
> # What I did is:
> 
> out <- matrix(NA,1,3)
> 
>  out[1,1] <- ( (sum(store<=M                ))  /length(store) )*100
>  out[1,2] <- ( (sum(store> M  & store<= N   ))  /length(store)
)*100
>  out[1,3] <- ( (sum(store> N                ))  /length(store) )*100
> 
> colnames(out)<-c("percent<=M","percent>M &
<=N","percent>N")
> out
> 
> But this gets very tedious if I have many cutoff-points. Does anybody know
a
> more elegant way to do this task?
> 
> Thanks so much.
> 
> Cheers,
> Jens
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
> 

-- 
Jim Holtman

What the problem you are trying to solve?

On Tue, 2005-07-26 at 15:48 -0400, jhainm at fas.harvard.edu
wrote:
> Hi,
> 
> I am looking for an elegant way to transform a vector into percentages of
values
> that meet certain criteria.
> 
> store<-c(1,1.4,3,1.1,0.3,0.6,4,5)
> 
> # now I want to get the precentages of values
> # that fall into the categories <=M , >M & <=N , >N
> # let
> M <-.8
> N <- 1.2
> # In my real example I have many more of these cutoff-points
> 
> # What I did is:
> 
> out <- matrix(NA,1,3)
> 
>   out[1,1] <- ( (sum(store<=M                ))  /length(store) )*100
>   out[1,2] <- ( (sum(store> M  & store<= N   )) 
/length(store) )*100
>   out[1,3] <- ( (sum(store> N                ))  /length(store) )*100
> 
> colnames(out)<-c("percent<=M","percent>M &
<=N","percent>N")
> out
> 
> But this gets very tedious if I have many cutoff-points. Does anybody know
a
> more elegant way to do this task?
> 
> Thanks so much.
> 
> Cheers,
> Jens
Something alone the lines of:

store <- c(1, 1.4, 3, 1.1, 0.3, 0.6, 4, 5)
M <- 0.8
N <- 1.2

x <- hist(store, br = c(min(store), M, N, max(store)), 
          plot = FALSE)$counts  

pct.x <- prop.table(x) * 100

names(pct.x) <- c("percent <= M","percent > M &
<= N","percent > N")
> pct.x
      percent <= M percent > M & <= N        percent > N 
                25                 25                 50 


I think that should do it. See ?hist for more information and take note
of the 'include.lowest' and 'right' arguments relative to
whether or not
values are or are not included in the specified intervals.

See ?prop.table as well.

Also be acutely aware of potential problems with exact equality
comparisons with floating point numbers and the break points...if you
have a float value equal to a breakpoint in your vector.

HTH,

Marc Schwartz

Why not write a function ? Here is one.

 mytable <- function(x, br){

   n  <- length(br)
  
   tb <- table( cut( x, breaks=c(-Inf, br, Inf) ) )
   tb <- 100 * tb / sum(tb)

   tb.n      <- paste( c("", br), c(br, ""), sep="
< x <= " )
   tb.n[1]   <- paste("x <= ", br[1], sep="")
   tb.n[n+1] <- paste("x > ",  br[n], sep="")

   names(tb) <- tb.n
   return(tb)
 }

 mytable( store, br=c(0.8, 1.2) )
       x <= 0.8 0.8 < x <= 1.2        x > 1.2
             25             25             50

You might want to do a bit more testing especially at the break points.
However I do not like the output of the above because the names of the
table overlaps. Here is another function that might have nicer output.

 mytable2 <- function(x, br){
   tb <- as.matrix( mytable( x=x, br=br ) )
   colnames(tb) <- "Percentage"
   return(tb)
 }

 mytable2( store, br=c(0.8, 1.2) )
                Percentage
 x <= 0.8               25
 0.8 < x <= 1.2         25
 x > 1.2                50

Hope this helps.

Regards, Adai



On Tue, 2005-07-26 at 15:48 -0400, jhainm at fas.harvard.edu
wrote:
> Hi,
> 
> I am looking for an elegant way to transform a vector into percentages of
values
> that meet certain criteria.
> 
> store<-c(1,1.4,3,1.1,0.3,0.6,4,5)
> 
> # now I want to get the precentages of values
> # that fall into the categories <=M , >M & <=N , >N
> # let
> M <-.8
> N <- 1.2
> # In my real example I have many more of these cutoff-points
> 
> # What I did is:
> 
> out <- matrix(NA,1,3)
> 
>   out[1,1] <- ( (sum(store<=M                ))  /length(store) )*100
>   out[1,2] <- ( (sum(store> M  & store<= N   )) 
/length(store) )*100
>   out[1,3] <- ( (sum(store> N                ))  /length(store) )*100
> 
> colnames(out)<-c("percent<=M","percent>M &
<=N","percent>N")
> out
> 
> But this gets very tedious if I have many cutoff-points. Does anybody know
a
> more elegant way to do this task?
> 
> Thanks so much.
> 
> Cheers,
> Jens
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
>