Using sparkTable to create plots with different frequencies

Question

I am trying to create a dashboard which looks something like the image just below:

It makes a cumulative plot for indices using weekly returns. Now i want to embed a barplot as additional column which plots returns at monthly frequency (assuming each month is 4 weeks). Is that possible ?

While adding returns up from 1 week to 4 weeks is easy, what sort of time values should I give and will it then lead to gaps in my barplot ?

Here is the code that I use for sparktable

content <- list(
     function(x) { tail(x,1) },
     function(x) {
        round(tail(x,1),2)
       },
     function(x) { round(max(x),2) },
     function(x) { round(min(x),2) },
     newSparkLine(lineWidth = 2, pointWidth = 6), newSparkBar()
)
names(content) <- c("Current", "LastWeek", "Max", "Min", "Cumulative","WeeklyRet")

dat<-reshapeExt(lpl,idvar="INDEX",varying=list(2))
 # set variables
 vars <- c("CLOSE", "WEEKLY", "CLOSE", "CLOSE","CLOSE" ,"WEEKLY")

 stab <- newSparkTable(dataObj = lpl, tableContent = content, varType = vars)

My data looks something like this

        id time   CLOSE     WEEKLY
1469 SP500    1 1987.66 -2.4184217
1476 SP500    2 1951.13 -1.8722484
1483 SP500    3 1952.29  0.0594174
1490 SP500    4 1990.20  1.9048337
1497 SP500    5 1932.24 -2.9996274
1504 SP500    6 1923.82 -0.4376709

What I want is weekly returns added for say weeks 1 to 4, 5 to 8 and then plotted as a separate column