Insert loop result into data frame

Question

I have a for loop which prints a result, just a single number and an i(for 1:10)

(count <- (length(which(colSums(data2[, -8])==0))))
print(i)

When I run all parts of the loop manually it prints the correct count(decreasing in value). And I could manually put all the values in excel to plot. However, Id like in my loop for count and i to be added to a new data frame, so I can run this a thousand times to get a reliable result.

And get a dataframe like this:

So my question basically is: how do I extract 'count' and 'i' and create a dataframe to fit this in(make a row for each i).

Datasets and the rest of the loop is irrelevant for the solution I think.

Any help would be appreciated, cheers Jasper

EDIT

My current loop

for(i in 1:10) {

data2 <- data2[-sample(nrow(data2),size=1,replace=FALSE),]
(count <- (length(which(colSums(data2[, -8])==0))))
print(i)

}

count is a single number, independent of i in the code you've written...? — Frank
– Frank, Commented May 18, 2015 at 14:34
Count is indeed a single number, independent of i. > (count <- (length(which(colSums(data2[, -8])==0)))) [1] 9 — Jasperovic
– Jasperovic, Commented May 18, 2015 at 14:36
i is like time, it samples 10 times random rows and calculates the amount of columns with 0. There are 10 different samples, so its always dead after 10 tries. — Jasperovic
– Jasperovic, Commented May 18, 2015 at 14:38
I think you'll need to actually write your loop for this to make sense. I think you have some data and within the loop create data2 <- data[sample(1:nrow(data),10),], but I can only guess. — Frank
– Frank, Commented May 18, 2015 at 14:48

Frank · Accepted Answer · 2015-05-18 15:15:45Z

1

A more efficient approach would be to compute the column sums first and difference for each sample:

cs <- colSums(data2[,-8])

nsim   <- 10
res    <- vector("integer",nsim)
for (i in 1:nsim) res[i] = sum(!(cs - data2[sample(1:nrow(data2),1),-8]))

simres <- data.frame(i=1:nsim,res=res)

Note that length(which(x)) is the same as sum(x) here; and x==0 is !x.

Comments. It might also be a good idea to store your data in a matrix if it is all numeric and operations like this are frequent.

There are many alternatives to for loops in R. Here's an example typical for simulations:

res <- replicate(nsim,sum(!(cs - data2[sample(1:nrow(data2),1),-8])))

If you're taking many samples, you could also precompute the row-left-out value for every row:

norowres <- rowSums(!(cs-data2[,-8])) # not tested
res      <- sample(norowres,nsim,replace=TRUE)

edited May 18, 2015 at 15:15

answered May 18, 2015 at 15:03

Frank

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3 Comments

Roland Over a year ago

Don't subset a data.frame in a for loop. It's more efficient to fill a vector and put it into a data.frame after the loop.

Frank Over a year ago

@Roland Good to know; I'll switch to that.

Jasperovic Over a year ago

Thanks, simres <- data.frame(i=1:nsim) was what I was looking for.

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