r - Testing multiple columns in a time series simultaneously - 


library("xts") data1<- cbind(a = c(1,2,3,4,5,6,5,4,3,4,5,6,5,4,3,5),               b = c(1,2,3,4,5,6,5,4,3,4,5,6,5,4,3,5),               c = c(1,2,3,4,5,6,5,4,5,4,5,4,5,4,5,2),               d = c(1,2,3,4,5,6,5,4,1,1,1,1,1,2,3,2)) data<- xts(data1, sys.date() - (16:1))  data             b c d 2013-07-09 1 1 1 1 2013-07-10 2 2 2 2 2013-07-11 3 3 3 3 2013-07-12 4 4 4 4 2013-07-13 5 5 5 5 2013-07-14 6 6 6 6 2013-07-15 5 5 5 5 2013-07-16 4 4 4 4 2013-07-17 5 3 5 1 2013-07-18 4 4 4 1 2013-07-19 5 5 5 1 2013-07-20 4 6 4 1 2013-07-21 5 5 5 1 2013-07-22 4 4 4 2 2013-07-23 3 3 5 3 2013-07-24 5 5 2 2

i have data set contains 100 such columns. need method or define function can tell me how many such columns are, above 5 days sma (moving average) on given day. if give specific date , 5 days sma, should number of columns above sma and, if possible, column names too.

you can use whichand tabulate, order, etc. 

all <- which(data>5, arr.ind=true) table(all[,"row"]) all[order(all[,"row"]),] split(all, all[,"row"])

edit: rolling mean, can calculate rolling mean first , procede mentioned above.

sra <- apply(data, 2, rollmean, k=5) <- which(sra>5, arr.ind=true)

edit2: can dates, if use rownames(all). 

table(rownames(all)) split(all, rownames(all))

edit3: apparently missunderstood question. problem names comes apply function. if use lapply instead, desired rownames. can cbind data na's first , last 2 days. 

sra <- do.call(cbind, lapply(data, rollmean, k=5)) sra <- cbind(sra, data)[, 1:ncol(sra)] <- which(sra>data, arr.ind=true)

edit4: note rollmean has align-argument. apparently want right-align (default center). 

sra <- do.call(cbind, lapply(data, rollmean, k=5, align="right")) sra <- cbind(sra, data)[, 1:ncol(sra)] <- which(sra>data, arr.ind=true)

edit 5: if sra of class xts, not have rownames , matrix all consequently not either. can use as.matrix(sra) rownames again. final line added in case want know names of columns instead of number. 

sra <- do.call(cbind, lapply(data, rollmean, k=5, align="right")) sra <- as.matrix(cbind(sra, data)[, 1:ncol(sra)]) <- which(sra>data, arr.ind=true) table(rownames(all)) split(all[,"col"], rownames(all)) lapply(split(all[,"col"], rownames(all)), function(x) colnames(data)[x])

edit 6: @ 1 particular date, save final list , specify date , extract date list. instance:

lst <- lapply(split(all[,"col"], rownames(all)), function(x) colnames(data)[x]) dat <- "2013-07-23" lst[dat]

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