Dear list members I have a rather large vector (part of a data frame) giving the time (date + time, POSIXct) of observations. The times are irregular (with both small and large jumps) but increasing, and there are several millions of them.
I now wish to reduce my data set, so that I only have observations which are at least (for example) 60 seconds apart. Basically, I need (all) the indices of my time variable where the difference in times are at least 60 seconds. I thought this would be a rather simple task, but perhaps I'm tired, for I couldn't figure out how to do it in a even moderately elegant way (not looping over all the values, which is quite slow). This solution seemed sensible: x=cumsum(diff(timevar) %/% 60) ind=c(1,cumsum(rle(x)$lengths)+1) # And perhaps removing the last value but doesn't work, as it only captures the 'first times' in each 60-second interval following the first time value, and thus may include times with values that are closer than 60 seconds. I also considered round.POSIXct and trunc.POSIXct, but these are not appropriate either, for obvious reasons. So, any ideas how to do this in an elegant and efficient way? -- Karl Ove Hufthammer ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
