Splitting row in function of time

Try this:  (it would have been easier if you had used 'dput' on your data)

x <- read.table('/temp/example.txt', skip = 1, as.is = TRUE)
# convert to POSIXct
x$beg <- as.POSIXct(paste(x$V4, x$V5))
x$end <- as.POSIXct(paste(x$V6, x$V7))
# determine breaks over midnight
x$over <- format(x$beg, "%d") != format(x$end, "%d")
x$V1 <- x$V4 <- x$V5 <- x$V6 <- x$V7 <- NULL  # remove extra columns
# put names on columns
names(x) <- c('phaseno', 'activity', 'phasetime', 'beg', 'end', 'over')
# extract records that extend over midnight
overSet <- subset(x, over)
normalSet <- subset(x, !over)

newSet <- do.call(rbind, lapply(seq_along(overSet$over), function(.row){
    # for each row, make two copies so you can change them individually
    .data <- overSet[c(.row, .row), ]  # two copies of the row
    .data$end[1] <- trunc(.data$end[1], units = 'days')
    .data$phasetime[1] <- as.numeric(.data$end[1]) - as.numeric(.data$beg[1])
    .data$beg[2] <- .data$end[1]
    .data$phasetime[2] <- as.numeric(.data$end[2]) - as.numeric(.data$beg[2])
    .data
}))
# combine the data and then sort by 'beg'
result <- rbind(normalSet, newSet)
result <- result[order(result$beg), ]


output:
      phaseno activity phasetime                 beg                 end  over
1           1        L     61033 2010-06-01 00:21:00 2010-06-01 17:18:13 FALSE
2           2        D      7907 2010-06-01 17:18:14 2010-06-01 19:30:01 FALSE
3           3        L       395 2010-06-01 19:30:02 2010-06-01 19:36:37 FALSE
4           4        D     15802 2010-06-01 19:36:38 2010-06-02 00:00:00  TRUE
4.1         4        D      2693 2010-06-02 00:00:00 2010-06-02 00:44:53  TRUE
5           5        W        40 2010-06-02 00:44:54 2010-06-02 00:45:34 FALSE
6           6        D      6425 2010-06-02 00:45:35 2010-06-02 02:32:40 FALSE
7           7        L       379 2010-06-02 02:32:41 2010-06-02 02:39:00 FALSE
8           8        D      1414 2010-06-02 02:39:01 2010-06-02 03:02:35 FALSE
9           9        W        73 2010-06-02 03:02:36 2010-06-02 03:03:49 FALSE

Hello all,

I have a data frame that looks like this:

http://r.789695.n4.nabble.com/file/n4077622/Capture.png

I would like to know if it's possible to split a single row into two rows
when the time frame between "beg" and "end" overlaps midnight. I want to
compare the frequency of each activity for each day so a row for a phase
that overlaps on two dates unbalances the graphs I create with this data.

Ex:

From the original row:

http://r.789695.n4.nabble.com/file/n4077622/Capture2.png

Note: "phasetime" is only a difftime between "end" and "beg".
? ? ? ? ?"phaseno" and "activity" should stay the same for the two new
lines.

Here is a sample of my data that covers a few days:
http://r.789695.n4.nabble.com/file/n4077622/example.txt example.txt

Thank you to anyone who takes the time to read this and any idea will be
welcome

PEL

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