rolling average to multiple variables in R using data.table package

Question

I would like to get rolling average for each of the numeric variables that I have. Using data.table package, I know how to compute for a single variable. But how should I revise the code so it can process multiple variables at a time rather than revising the variable name and repeat this procedure for several times? Thanks.

Suppose I have other numeric variables named as "V2", "V3", and "V4".

require(data.table)
setDT(data)
setkey(data,Receptor,date)
data[ , `:=` ('RollConc' = rollmean(AvgConc, 48, align="left", na.pad=TRUE)) , by=Receptor]

A copy of my sample data can be found at: https://drive.google.com/file/d/0B86_a8ltyoL3OE9KTUstYmRRbFk/view?usp=sharing

I would like to get 5-hour rolling means for "AvgConc","TotDep","DryDep", and "WetDep" by each receptor.

Answer 1

From your description you want something like this, which is similar to one example that can be found in one of the new vignettes:

library(data.table)
set.seed(42)
DT <- data.table(x = rnorm(10), y = rlnorm(10), z = runif(10), g = c("a", "b"), key = "g")
library(zoo)
DT[, paste0("ravg_", c("x", "y")) := lapply(.SD, rollmean, k = 3, na.pad = TRUE), 
   by = g, .SDcols = c("x", "y")]

Answer 2

Now, one can use the frollmean function in the data.table package for this.

library(data.table)
set.seed(42)
DT <- data.table(x = rnorm(10), y = rlnorm(10), z = runif(10), 
                                g = c("a", "b"), key = "g")

xy <- c("x", "y")
DT[, (xy):= lapply(.SD, frollmean, n = 3, fill = NA, align="center"), 
                                   by = g, .SDcols =  xy]

Here, I am replacing the x and y columns by the rolling average.