How to group Time Series data into round intervals of 5 minutes in R? -

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i have time series data frame looking this:

  time                 source  value 1 2016-01-20 15:10:04  c04     open 2 2016-01-20 15:09:57  m04     true 3 2016-01-20 15:09:53  m02     true 4 2016-01-20 15:09:53  m03     true 5 2016-01-20 14:44:54  m04     true

now group them in intervals of 5 minutes starting 00:00:00, intervals of 0-5-10-15-20... , on. intervals shall used later group identifier:

  time                 source  value  group 1 2016-01-20 15:10:04  c04     open   10 2 2016-01-20 15:09:57  m04     true   5 3 2016-01-20 15:09:53  m02     true   5 4 2016-01-20 15:09:53  m03     true   5 5 2016-01-20 14:44:54  m04     true   40

i tried cut() dates using breaks="5 min" instead of getting round start , end values, result looks this:

 > table(cut.posixt(df.formatted$time, breaks="5 min"))[1:5]  2015-12-31 12:49:00 2015-12-31 12:54:00 2015-12-31 12:59:00 2015-12-31 13:04:00 2015-12-31 13:09:00                4                   0                   0                   1                  15

is there way tell cut() use round time intervals? tried grouping using xts package, got more confused ohlc helped me. tried using her.misc package (see time.factor documentation due poor documentation couldn't run properly.

does maybe know how solve problem?

first, need install "chron" package. package has minutes() function gives minute of time.

i have paste first , second column don't think have too. use tmptime <- tmp[,1]

library(chron)  tmp <- read.table(text="time  source  value  2016-01-20 15:10:04  c04     open  2016-01-20 15:09:57  m04     true  2016-01-20 15:09:53  m02     true  2016-01-20 15:09:53  m03     true  2016-01-20 14:44:54  m04     true", header=t, row.names= null)  tmptime <- paste(tmp[,1], tmp[,2])  group <- seq(0,55,5)  sapply(tmptime, function(x){   x <- minutes(x)   for(i in 2:length(group)){     if(x < group[i]) {return(group[i-1]); break}     else if(x >= group[length(group)]) return(group[length(group)])   } })  [1] 10  5  5  5 40

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