R: How to split a chron date & time object in zoo for aggregation

Question

I have imported data with a five minute interval into a zoo object, where the index is a chron with both date and time:

> d
(09/09/09 16:45:10)  13.2  5.8
(09/09/09 16:50:10)   8.3  0.7
(09/09/09 16:55:10)   4.7  0.7
(09/09/09 17:00:10)   6.6  0.7
(09/09/09 17:05:10)   4.6  0.7

I am trying to aggregate by quarter hour intervals.

I found way to do so by converting back to a string, but the output is no longer a zoo.

> r =data.frame(aggregate(d,trunc(chron(times=substr(as.character(index(d)),11,18)),"00:15:00"), mean)
> r
00:00:00   0.5644444
00:15:00   0.5400000
00:30:00   0.5488889
00:45:00   0.6155556
01:00:00   0.3422222

While I can plot this, I was trying to do this natively. I found that aggregate with zoo could do day and hour, but I could not subdivide the hour.

Answer 1

I don't believe that there's any way to do this built into zoo or chron, but you can create your own function by using a little math. Here you go:

trunc.minutes <- function (x, n.minutes) 
{
    if (!inherits(x, "times")) 
        x <- as.chron(x)
    x <- as.numeric(x)
    sec <- round(24 * 3600 * abs(x - floor(x)))
    h <- (sec%/%(n.minutes*60))/(60/n.minutes)
    hour <- as.integer(h)
    minutes <- (h %% hour) * 60
    chron(dates=chron::dates(x), times=times(paste(hour, minutes, "00", sep=":")))
}

Here's an example of the usage:

dts <- chron::dates(c("02/27/92", "02/27/92", "01/14/92",
                "02/28/92", "02/01/92"))
tms <- times(c("23:03:20", "23:29:56", "01:03:30",
                "18:21:03", "16:56:26"))     
x <- chron(dates = dts, times = tms) # original dates
x
[1] (02/27/92 23:03:20) (02/27/92 22:29:56) (01/14/92 01:03:30)
[4] (02/28/92 18:21:03) (02/01/92 16:56:26)
trunc.minutes(x, 15) # new dates at 15 minute intervals
[1] (02/27/92 23:00:00) (02/27/92 22:15:00) (01/14/92 01:00:00)
[4] (02/28/92 18:15:00) (02/01/92 16:45:00)
trunc.minutes(x, 30) # new dates at 30 minute intervals
[1] (02/27/92 23:00:00) (02/27/92 22:00:00) (01/14/92 01:00:00)
[4] (02/28/92 18:00:00) (02/01/92 16:30:00)

Lastly, you can now use this function to aggregate the data:

ts.zoo <- zoo(rnorm(5), x) # a zoo time series

Or just use these new dates for aggregation (see how it rolls up the second example since there are two values in that window):

> aggregate(ts.zoo, trunc.minutes(x, 15), mean)
(01/14/92 01:00:00) (02/01/92 16:45:00) (02/27/92 23:00:00) (02/27/92 23:15:00) 
         -0.6738659          -0.4844803           0.7968155          -1.3571121 
(02/28/92 18:15:00) 
          0.7625861 
> aggregate(ts.zoo, trunc.minutes(x, 30), mean)
(01/14/92 01:00:00) (02/01/92 16:30:00) (02/27/92 23:00:00) (02/28/92 18:00:00) 
         -0.6738659          -0.4844803          -0.2801483           0.7625861 

Answer 2

chron has a trunc.times method so we can do this:

library(zoo)
library(chron)
z <- zoo(1:5, 
   chron(c("02/27/92", "02/27/92", "01/14/92", "02/28/92", "02/01/92"),
   c("23:03:20", "23:29:56", "01:03:30", "18:21:03", "16:56:26")))
aggregate(z, function(x) trunc(x, "00:15:00"), mean)

Answer 3

Hello all,

REally intersting post, I am new in R and I'd like to get some data analysis, I have a data files with rows of time stamp and values like:"2008-10-01 00:00:15 12 12 13 13" and I'd like to do some analysis like; median values every 10 minutes per example, median value per day, or per month...

I'd like any comment about it. thanks