R和Data.table-在多个列上应用rollapply

Question

I would really appreciate if you can help me do the rollapply for each column of the data.table

    time                AUD NZD   EUR GBP    USD AUD 

1   2013-01-01 20:00    0.213     -0.30467   -0.127515 
2   2013-01-01 20:05    0.21191   -0.30467   -0.127975 
3   2013-01-01 20:10    0.212185  -0.304965  -0.127935 
4   2013-01-01 20:15    0.212055  -0.30511   -0.1288 
5   2013-01-01 20:20    0.211225  -0.30536   -0.12938 
6   2013-01-01 20:25    0.211185  -0.30527   -0.129195 
7   2013-01-01 20:30    0.21159   -0.3059    -0.13043 
8   2013-01-01 20:35    0.21142   -0.304955  -0.13155 
9   2013-01-01 20:40    0.21093   -0.30419   -0.132715 
10  2013-01-01 20:45    0.2078    -0.30339   -0.13544
11  2013-01-01 20:50    0.208445  -0.30304   -0.135645
12  2013-01-01 20:55    0.208735  -0.30185   -0.1357 
13  2013-01-01 21:00    0.20891   -0.303265  -0.13722 
14  2013-01-01 21:05    0.20903   -0.30428   -0.137495
15  2013-01-01 21:10    0.209615  -0.305495  -0.13734 
16  2013-01-01 21:15    0.20981   -0.30588   -0.13772 
17  2013-01-01 21:20    0.209855  -0.306935  -0.13801
18  2013-01-01 21:25    0.209585  -0.30604   -0.138045 
19  2013-01-01 21:30    0.210105  -0.3061    -0.137765 
20  2013-01-01 21:35    0.210335  -0.30734   -0.138525 

Code that works:

library("zoo")
library("data.table")

calculateAverage <- function (x,N) {
        tempDataStorage <- rollapply(out[,1], N, mean)
}

col1 <- out[,2]
col2 <- out[,3]
col3 <- out[,4]

average1 <- calculateAverage(col1, 2)
average2 <- calculateAverage(col2, 2)
average3 <- calculateAverage(col3, 2)

combine <- cbind(average1, average2, average3)
tempMatrix <- matrix(, nrow = nrow(out), ncol = ncol(out))
tempMatrix[2:nrow(out), 1:3] <- combine

Suggestion from SO :

test <- lapply(out[,with=F], function(x) rollapply(x,width=2, FUN=mean))

Challenges: 1. The code I created works, but it feels inefficient and not generic. It needs to be modified whenever the number of cols changes 2. Suggestion from SO output is list which is not useful to me

If an alternate method is suggested, I would be really appreciate it!

Thanks in advance Edit: Data table added

Answer 1

data <- cbind(mtcars,as.Date(c("2007-06-22", "2004-02-13")))
merge(rollapply(Filter(is.numeric, data), 2, mean),
      Filter(Negate(is.numeric), data))

The first line creates data, so that there are not only numeric values in it. This is only to mimic your data, which is not available right now.

The second line filters only numeric columns and applies mean function to each of filtered columns.

Answer 2

Suggestion from David Arenburg worked perfectly!

MaPrice <- function(x, N) {
    Mavg <- rollapply(x, N, mean)
    Mavg
}

SpreadMA <- out[, lapply(.SD, MaPrice, N = 20)]