R help - Dec 2009 - Counting Frequencies

Hi - I'm having difficulty with frequencies in R. I have a table with a
variable (column) called "difference" 600 observations (rows). I would
like
to know how many values are < -0.5 as well as how many are > 0.5. The rest
are obviously in the middle.

In SAS I could this immediately but am unable to do it in R.

Thanks for your help.
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> x <- runif(10, 0, 1)
> x2 <- x > 0.5
> x2
 [1]  TRUE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE
FALSE
> table(x2)
x2
FALSE  TRUE
    5     5


On Wed, Dec 9, 2009 at 6:36 PM, BIGBEEF <martin.bezener@gmail.com> wrote:
>
> Hi - I'm having difficulty with frequencies in R. I have a table with a
> variable (column) called "difference" 600 observations (rows). I
would like
> to know how many values are < -0.5 as well as how many are > 0.5. The
rest
> are obviously in the middle.
>
> In SAS I could this immediately but am unable to do it in R.
>
> Thanks for your help.
> --
> View this message in context:
> http://n4.nabble.com/Counting-Frequencies-tp956556p956556.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@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.
>


-- 
=============================WenSui Liu
Blog   : statcompute.spaces.live.com
Tough Times Never Last. But Tough People Do.  - Robert Schuller
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On 12/10/2009 10:36 AM, BIGBEEF wrote:
> Hi - I'm having difficulty with frequencies in R. I have a table with a
> variable (column) called "difference" 600 observations (rows). I
would like
> to know how many values are<  -0.5 as well as how many are>  0.5. The
rest
> are obviously in the middle.
>
> In SAS I could this immediately but am unable to do it in R.
>    
Hi Martin,

difference<-runif(100)*2-1
table(cut(difference,
  breaks=c(min(difference)-0.1,-0.5,0.5,max(difference))))

The "-0.1" is to ensure that the lowest value is included in the cut.

Jim