[R] looking for 'tied rows' in dataframe

Evan Cooch ev@n@cooch @end|ng |rom gm@||@com
Mon Mar 18 01:00:27 CET 2019


Got relatively close - below:

On 3/17/2019 7:39 PM, Evan Cooch wrote:
> Suppose I have the following sort of structure:
>
> test <- matrix(c(2,1,1,2,2,2),3,2,byrow=T)
>
> What I need to be able to do is (i) find the maximum value for each 
> row, (ii) find the column containing the max, but (iii) if the maximum 
> value is a tie (in this case, all numbers of the row are the same 
> value), then I want which.max (presumably, a tweaked version of what 
> which.max does) to reurn a T for the row where all values are the same.
>
> Parts (i) and (ii) seem easy enough:
>
> apply(test,1,max)  --- gives me the maximum values
> apply(test,1,which.max) --- gives me the column
>
> But, standard which.max doesn't handles ties/duplicates in a way that 
> serves my need. It defaults to returning the first column containing 
> the maximum value.
>
> What I'd like to end up with is, ultimately, something where 
> apply(test,1,which.max) yields 1,2,T  (rather than 1,2,1).
>
> So, a function which does what which.max currently does if the 
> elements of the row differ, but which returns a T (or some such) if in 
> fact the row values are all the same.
>
> I've tried a bunch of things, to know avail. Closest I got was to use 
> a function to test for whether or not a vector
>
> isUnique <- function(vector){
>                  return(!any(duplicated(vector)))
>             }
>
> which returns TRUE if values of vector all unique. So
>
> apply(test,1,isUnique)
>
> returns
>
> [1]  TRUE  TRUE FALSE
>
> but I'm stuck beyond this. 

The following gets me pretty close,

test_new <- test
test_new[which(apply(test,1,isUnique)==FALSE),] <- 'T'

but is clunky.



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