find corresponding dateTime in several time series in R - r

Question

I am an R newbie and am finding the conversion from matlab rather tricky, so apologies in advance for what could be a very simple question.
I am analyzing some time series data and the problem outlined below demonstrates the problem I am having in R:
Dat1 <- data.frame(dateTime = as.POSIXct(c("2012-05-03 00:00","2012-05-03 02:00",
"2012-05-03 02:30","2012-05-03 05:00",
"2012-05-03 07:00"), tz = 'UTC'),x1 = rnorm(5))
Dat2 <- data.frame(dateTime = as.POSIXct(c("2012-05-03 01:00","2012-05-03 01:30",
"2012-05-03 02:30","2012-05-03 06:00",
"2012-05-03 07:00"), tz = 'UTC'),x1 = rnorm(5))
Dat3 <- data.frame(dateTime = as.POSIXct(c("2012-05-03 00:15","2012-05-03 02:20",
"2012-05-03 02:40","2012-05-03 06:25",
"2012-05-03 07:00"), tz = 'UTC'),x1 = rnorm(5))
Dat4 <- data.frame(dateTime = as.POSIXct(c("2010-05-03 00:15","2010-05-03 02:20",
"2010-05-03 02:40","2010-05-03 06:25",
"2010-05-03 07:00"), tz = 'UTC'),x1 = rnorm(5))
So, here I have 5 data frames where all of the data are measured at similar times. I am now trying to ensure that all of the data frames have an identical time step i.e. all measured at the same time. I can do this for two data frames:
idx1 <- (Dat1[,1] %in% Dat2[,1])
which will tell me the index of the consistent times in these two data frames. I can then re-define the data frame by
newDat1 <- Dat1[idx1,]
to get the data desired.
My question now is, how do I apply this to all of the data frames i.e. more than 2. I have tried:
idx1 <- (Dat1[,1] %in% (Dat2[,1] %in% (Dat3[,1] %in% Dat4[,1])))
but I can see that this is completely wrong. Any suggestions? Please keep in mind that I have many data frames (more than five), where each contain different variables.
EDIT:
I may have found one way this can be done:
idx1 <- (Dat1[,1] %in% intersect(intersect(intersect(Dat1[,1],Dat2[,1]),Dat3[,1]),Dat4[,1]))
which will give the index, and can be used to define a new variable:
Dat1 <- Dat1[idx1,]
Dat2 <- Dat2[idx1,]
Dat3 <- Dat3[idx1,]
Dat4 <- Dat4[idx1,]
Although this work for this example, I was hoping to find a way of making this work for n number of data frames without having to write repeat this n number of times

Answer 1

To identify timestamps that are common to all data frames, create a function to return the intersection of multiple vectors
intersectMulti <- function(x=list()){
for(i in 2:length(x)){
if(i==2) foo <- x[[i-1]]
foo <- intersect(foo,x[[i]]) #find intersection between ith and previous
}
return(x[[1]][match(foo, x[[1]])]) #get original to retain format
}
Note that there are no common timestamps among the four dataframes in the question
> intersectMulti(x=list(Dat1[,1],Dat2[,1],Dat3[,1],Dat4[,1]))
character(0)
But there is one common timestamp in the first three dataframes
> intersectMulti(x=list(Dat1[,1],Dat2[,1],Dat3[,1]))
[1] "2012-05-03 07:00:00 UTC"
Use the result from the function to subset rows of each dataframe with common timestamp:
m <- intersectMulti(x=list(Dat1[,1],Dat2[,1],Dat3[,1]))
Dat1 <- Dat1[Dat1$dateTime %in% m,]
Dat2 <- Dat2[Dat2$dateTime %in% m,]
Dat3 <- Dat3[Dat3$dateTime %in% m,]
Dat4 <- Dat4[Dat4$dateTime %in% m,]
> Dat1
dateTime x1
5 2012-05-03 07:00:00 -0.1607363
> Dat2
dateTime x1
5 2012-05-03 07:00:00 -0.2662494
> Dat3
dateTime x1
5 2012-05-03 07:00:00 -0.1917905

Answer 2

If this works for you:
idx1 <- (Dat1[,1] %in% intersect(intersect(intersect(Dat1[,1],Dat2[,1]),Dat3[,1]),Dat4[,1]))
then try this, it works on lists/vectors and more elegant:
idx1 <- Dat1[,1] %in% Reduce(intersect, list(Dat1[,1], Dat2[,1], Dat3[,1], Dat4[,1]))