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Im having some troubles using factors in functions, or just to make use of them in basic calculations. I have a data-frame something like this (but with as many as 6000 different factors). 

df<- data.frame( p <- runif(20)*100, q = sample(1:100,20, replace = T), tt = c("e","e","f","f","f","i","h","e","i","i","f","f","j","j","h","h","h","e","j","i"), ta = c("a","a","a","b","b","b","a","a","c","c","a","b","a","a","c","c","b","a","c","b")) colnames(df)<-c("p","q","ta","tt")

Now price = p and quantity = q are my variables, and tt and ta are different factors.

Now, I would first like to find the average price per unit of q by each different factor in tt

(p*q ) / sum(q) by tt

This would in this case give me a list of 3 different sums, by a, b and c (I have 6000 different factors so I need to do it smart :) ).

I have tried using split to make lists, and in this case i can get each individual tt factor to contain the prices and another for the quantity, but I cant seem to get them to for example make an average. I've also tried to use tapply, but again I can't see how I can incorporate factors into this?

EDIT: I can see I need to clearify:

I need to find 3 sums, the average price pr. q given each factor, so in this simplified case it would be:

a: Sum of p*q for (Row (1,2,3, 7, 11, 13,14,18) / sum (q for row Row (1,2,3, 7, 11, 13,14,18)

So the result should be the average price for a, b and c, which is just 3 values.

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2 Answers 2

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I'd use plyr to do this:

library(plyr) ddply(df, .(tt), mutate, new_col = (p*q) / sum(q)) p q ta tt new_col 1 73.92499 70 e a 11.29857879 2 58.49011 60 e a 7.66245932 3 17.23246 27 f a 1.01588711 4 64.74637 42 h a 5.93743967 5 55.89372 45 e a 5.49174103 6 25.87318 83 f a 4.68880732 7 12.35469 23 j a 0.62043207 8 1.19060 83 j a 0.21576367 9 84.18467 25 e a 4.59523322 10 73.59459 66 f b 10.07726727 11 26.12099 99 f b 5.36509998 12 25.63809 80 i b 4.25528535 13 54.74334 90 f b 10.22178577 14 69.45430 50 h b 7.20480246 15 52.71006 97 i b 10.60762667 16 17.78591 54 i c 5.16365066 17 0.15036 41 i c 0.03314388 18 85.57796 30 h c 13.80289670 19 54.38938 44 h c 12.86630433 20 44.50439 17 j c 4.06760541

plyr does have a reputation for being slow, data.table provides similar functionality, but much higher performance.

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I need to divide p*q with the total sum of all the variables that belong to the factor a, b and c and so forth. So in my example im looking for 3 sums. I guess I should try to clearify.
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If I understood corectly you'r problem this should be the answer. Give it a try and responde, that I can adjust it if it's needed.

myRes <- function(tt) { out <- NULL; qsum <- sum(as.numeric(df[,"q"])) psum <- sum(as.numeric(df[,"p"])) for (var in tt) { index <- which(df["tt"] == var) out <- c(out, ((qsum *psum) / sum(df[index,"q"]))) } return (out) } threeValue <- myRes(levels(df[, "tt"]));
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4 Comments

Have you checked if this solution?
Ya, I might be missing something, but, Im looking for 3 values, not 20 as I get from this function. I've updated the question.
I get a error at the very last line, "Error in [.data.frame(df, index, "q") : object 'index' not found"`
I was in hurry sorry. Now it should be fine!

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