R and appending to data frames - r

Question

I have some cross correlation function crosscor, and I would like to loop through the function for each of the columns I have in my data matrix. The function outputs some cross correlation that looks something like this each time it is run:
Lags Cross.Correlation P.value
1 0 -0.0006844958 0.993233547
2 1 0.1021006478 0.204691627
3 2 0.0976746274 0.226628526
4 3 0.1150337867 0.155426784
5 4 0.1943150900 0.016092041
6 5 0.2360415470 0.003416147
7 6 0.1855274375 0.022566685
8 7 0.0800646242 0.330081900
9 8 0.1111071269 0.177338885
10 9 0.0689602574 0.404948252
11 10 -0.0097332533 0.906856279
12 11 0.0146241719 0.860926388
13 12 0.0862549791 0.302268025
14 13 0.1283308019 0.125302070
15 14 0.0909537922 0.279988895
16 15 0.0628012627 0.457795228
17 16 0.1669241304 0.047886605
18 17 0.2019811994 0.016703619
19 18 0.1440124960 0.090764520
20 19 0.1104842808 0.197035340
21 20 0.1247428178 0.146396407
I would like put all of the lists together so they are in a data frame, and ultimately export it into a csv file so the columns are as follows: lags.3, cross-correlation.3, p-value.3, lags.3, cross-correlation.2....etc. until p.value.50.
I have tried to use do.call as follows, but have not been successful:
for(i in 3:50)
{
l1<-crosscor(data[,2], data[,i], lagmax=20)
ccdata<-do.call(rbind, l1)
cat("Data row", i)
}
I've also tried just creating the data frame straight out, but am just getting the lag column names:
ccdata <- data.frame()
for(i in 3:50)
{
ccdata[i-2:i+1]<-crosscor(data[,2], data[,i], lagmax=20)
cat("Data row", i)
}
What am I doing wrong? Or is there an online source on data sets I could access to figure out how to do this? Best,

Answer 1

There is a transpose method for data.frames. If "crosscor" is the name of the object just try this:
tcrosscor <- t(crosscor)
write.csv(tcrosscor, file="my_crosscor_1.csv")
The first row would be the Lag's; the second row, the Cross.Correlation's; the third row the P.value's. I suppose you could "flatten" it further so it would be entirely "horizontal" or "wide". Seems painful but this might go something like:
single_line <- as.data.frame(unlist(tcrosscor))
names(single_line) <- paste("Lag", 'Cross.Correlation', 'P.value'), rep(1:50, 3), sep=".")
write.csv(single_line, file="my_single_1.csv")