Time series data arrangement - r

Question

I have several time series data and I'm trying to make a arrangement before further analysis. The point is that, as you can see in the picture, 3 financial time series has a different dates-observed. I want to eliminate whole line if there's at least 1 blanked line. In order to make a arrangement, first I made whole dates line to the left side except saturdays and sundays from 1 Jan 2005 to 30 Jun 2015 for indexing.
example: at the 11th row, there exist unmatched dates. I want to put NA columns in the middle.
here's what I've tried
Day=data.frame(test[,1:2])
Rk=data.frame(test[,3:4])
Vix=data.frame(test[,5:6])
BA=data.frame(test[,7:8])
i=1
k=0
while(i<=2736){
if(Day[i,1]==Rk[i,1]){i=i+1}
else if(Day[i,1]!=Rk[i,1]){
k=k+1
Rk[i+1:k+2634,]=Rk[i:k+2633,]
Rk[i,]=c(Day[i,1],NA)
i=i+1}
}
but it shows error message: number of items to replace is not a multiple of replacement length
I will be very much appreciated. Any kind of helps will be more than welcomed.

Answer 1

This is fairly easy if you use a time-series class like xts (or zoo).
# create sample data
set.seed(21)
dayone <- as.Date("2005-01-03")
plusdays <-c(0:4, 7:11, 14:18, 21:24)
test <- data.frame(date=dayone + plusdays)
test$day <- weekdays(test$date, abbreviate=TRUE)
test$date.1 <- dayone + c(plusdays[-11L], 25)
test$Kernel <- rnorm(nrow(test), 3e-5, 1e-6)
test$date.2 <- dayone + c(plusdays[-11L], 25)
test$VIX.High <- round(rnorm(nrow(test), 14, 0.1), 2)
test$date.3 <- dayone + c(plusdays[-11L], 25)
test$Baa.Aaa <- round(rnorm(nrow(test), 0.66, 0.01), 2)
require(xts)
# create xts objects for each column
Rk <- xts(test['Kernel'], test$date.1)
Vix <- xts(test['VIX.High'], test$date.2)
Ba <- xts(test['Baa.Aaa'], test$date.3)
# use xts to merge data
testxts <- merge(xts(,test$date), Rk, Vix, Ba)
I've left out your day column because xts/zoo objects are just a matrix with an index attribute, and you cannot mix types in a matrix. But you can use the .indexwday function to extract the weekday of each row.