Hi everybody,
I am amazed how quick i got my answer ;-) I have to recognize that Gabor's code
really puts to shame my skills in doing any programming in R. Is there any book
or documentation which really explains in details all these neat tricks from
{stats} like ave (i even didn't know this function existed), apply and all its
friends (sapply, tapply, etc) ? To be honest it took me quite a while to come
up with the "fancy" subscripting to get my persantages ;-))
thank you so much, i really appreciate your help,
Monica
> Date: Thu, 13 Mar 2008 09:45:05 -0400
> From: [EMAIL PROTECTED]
> To: [EMAIL PROTECTED]
> Subject: Re: [R] a more elegant way to get percentages?
> CC: r-help@r-project.org
>
> Assuming your x is as follows:
>
> x <- data.frame(locat = c("a", "b", "b", "c", "c", "c", "c", "d", "d", "d"),
> val = c(5, 5, 15, 5, 20, 5, 10, 5, 15, 10))
>
> Try this:
>
> x$percent1 <- ave(x$val, x$locat, FUN = function(x) 100*x/sum(x))
>
> On Thu, Mar 13, 2008 at 9:36 AM, Monica Pisica wrote:
>>
>> Hi,
>>
>> I am trying to get percentages in a more elegant way. I have a data.frame
>> with locations and values (counts) of species at that location. Each
>> location is repeated for each species i have values for and i would like to
>> get percentages of each species at that location. I am not sure if i am
>> clear in my explanations so i will paste my code below:
>>
>> #####################
>>
>>> x
>> locat val
>> 1 a 5
>> 2 b 5
>> 3 b 15
>> 4 c 5
>> 5 c 20
>> 6 c 5
>> 7 c 10
>> 8 d 5
>> 9 d 15
>> 10 d 10
>>> loc1 <- x$locat
>>> n <- length(loc1)
>>> locuniq1 <- unique(loc1)
>>> m <- length(locuniq1)
>>> counts <- seq(1:m)
>>>
>>> for (i in 1:m) {
>> + count <- 0
>> + for (j in 1:n) {
>> + if (loc1[j]==locuniq1[i]) count <- count+1
>> + counts[i] <- count
>> + }
>> + }
>>>
>>> percent1 <- rep(0,n)
>>> j <- 0
>>> for (i in 1:m) {
>> +
>> + b <- x[(j+1):(j+counts[i]),]
>> + total <- sum(b$val)
>> + percent1[(j+1):(j+counts[i])] <- round(apply(as.matrix(b$val), 1,
>> function(x) {x*100/total}),2)
>> + j = j+counts[i]
>> + }
>>> x1 <- cbind(x, percent1) # this is the result i want
>>> x1
>> locat val percent1
>> 1 a 5 100.00
>> 2 b 5 25.00
>> 3 b 15 75.00
>> 4 c 5 12.50
>> 5 c 20 50.00
>> 6 c 5 12.50
>> 7 c 10 25.00
>> 8 d 5 16.67
>> 9 d 15 50.00
>> 10 d 10 33.33
>>>
>> ################
>>
>> I am wondering if there is any way to do it more efficiently, much more that
>> the first loop which gives how many times each location is present in the
>> data.frame is slow if you have a larger data.frame and not only 10 rows.
>>
>> Thanks for any input and sorry if the email is on the long side,
>>
>> Monica
>>
>>
>> _________________________________________________________________
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>>
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>>
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