[R] truncating values into separate categories

Bill.Venables at csiro.au Bill.Venables at csiro.au
Fri Jul 31 03:31:30 CEST 2009


Here is a suggestion:

> Per <- c("NA", "1", "2", "3","4")
> NP <- c(1,  1,  2,  1, 1,  2,  2,  1,  4,  1,  0,  5,  
+ 3,  3,  1,  5,  3, 5, 1, 6, 1, 2, 2, 2,
+ 4, 4, 1, 2, 1, 3, 3, 1,  2,  2,  1,  2, 1, 2,
+ 2, 3, 1, 1, 4, 4, 1, 1, 1, 2, 2, 2)
> Person_CAT <- cut(NP, breaks = c(0:4, Inf)-0.5, labels = Per)
> table(Person_CAT)
Person_CAT
NA  1  2  3  4 
 1 19 15  6  9 
>  

You should be aware, though, that items corresponding to the level "NA" will NOT be treated as missing.


Bill Venables
http://www.cmis.csiro.au/bill.venables/ 


-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of PDXRugger
Sent: Friday, 31 July 2009 9:54 AM
To: r-help at r-project.org
Subject: [R] truncating values into separate categories


Hi all, 
  Simple question which i thought i had the answer but it isnt so simple for
some reason.  I am sure someone can easily help.  I would like to categorize
the values in NP into 1 of the five values in "Per", with the last
category("4") representing values >=4(hence 4:max(NP)).  The problem is that
R is reading max(NP) as multiple values instead of range so the lengths of
the labels and the breaks are not matching.  Suggestions?

Per <- c("NA", "1", "2", "3","4")

NP=c(1 ,1 ,2 ,1, 1 ,2 ,2 ,1 ,4 ,1 ,0 ,5 ,3 ,3 ,1 ,5 ,3, 5, 1, 6, 1, 2, 2, 2,
4, 4, 1, 2, 1, 3, 3, 1 ,2 ,2 ,1 ,2, 1, 2,
2, 3, 1, 1, 4, 4, 1, 1, 1, 2, 2, 2)

Person_CAT <- cut(NP, breaks=c(0,1,2,3,4:max(NP)), labels=Per)

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