# [R] categorizing data

Bill Dunlap w||||@mwdun|@p @end|ng |rom gm@||@com
Sun May 29 21:44:16 CEST 2022

```You could write a function that deals with one row of your data, based on
the order() function.  E.g.,
> to_10_30_50
function(x) {
stopifnot(is.numeric(x), length(x)==3, sum(x)==90, all(x>0))
c(10,30,50)[order(x)]
}
<bytecode: 0x000001912dcd1bd8>
> to_10_30_50(c(23,41,26))
[1] 10 50 30
Then loop over the rows.  Since this is a data.frame and not a matrix, you
need to coerce each row from a single-row data.frame to a numeric vector:
> data <- data.frame(tree=c(32,23,49), shrub=c(11,41,23),
grass=c(47,26,18))
> for(i in 1:nrow(new)) data[i,] <- to_10_30_50(as.numeric(data[i,]))
> data
tree shrub grass
1   30    10    50
2   10    50    30
3   50    30    10

-Bill

On Sun, May 29, 2022 at 12:29 PM Janet Choate <jsc.eco using gmail.com> wrote:

> Hi R community,
> I have a data frame with three variables, where each row adds up to 90.
> I want to assign a category of low, medium, or high to the values in each
> row - where the lowest value per row will be set to 10, the medium value
> set to 30, and the high value set to 50 - so each row still adds up to 90.
>
> For example:
> Data: Orig
> tree  shrub  grass
> 32     11       47
> 23      41      26
> 49      23      18
>
> Data: New
> tree  shrub  grass
> 30      10      50
> 10       50     30
> 50       30     10
>
> I am not attaching any code here as I have not been able to write anything
> effective! appreciate help with this!
> thank you,
> JC
>
> --
>
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>
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