Question

I am attempting to perform a study on the clustering of high/low points based on time. I managed to achieve the above by using to.daily on intraday data and merging the two using:

intraday.merge <- merge(intraday,daily)
intraday.merge <- na.locf(intraday.merge)
intraday.merge <- intraday.merge["T08:30:00/T16:30:00"] # remove record at 00:00:00

Next, I tried to obtain the records where the high == daily.high/low == daily.low using:

intradayhi <- test[test$High == test$Daily.High]
intradaylo <- test[test$Low == test$Daily.Low]

Resulting data resembles the following:

                     Open  High   Low Close Volume Daily.Open Daily.High Daily.Low Daily.Close Daily.Volume
2012-06-19 08:45:00 258.9 259.1 258.5 258.7   1424      258.9      259.1     257.7       258.7        31523
2012-06-20 13:30:00 260.8 260.9 260.6 260.6   1616      260.4      260.9     259.2       260.8        35358
2012-06-21 08:40:00 260.7 260.8 260.4 260.5    493      260.7      260.8     257.4       258.3        31360
2012-06-22 12:10:00 255.9 256.2 255.9 256.1    626      254.5      256.2     253.9       255.3        50515
2012-06-22 12:15:00 256.1 256.2 255.9 255.9    779      254.5      256.2     253.9       255.3        50515
2012-06-25 11:55:00 254.5 254.7 254.4 254.6   1589      253.8      254.7     251.5       253.9        65621
2012-06-26 08:45:00 253.4 254.2 253.2 253.7   5849      253.8      254.2     252.4       253.1        70635
2012-06-27 11:25:00 255.6 256.0 255.5 255.9    973      251.8      256.0     251.8       255.2        53335
2012-06-28 09:00:00 257.0 257.3 256.9 257.1    601      255.3      257.3     255.0       255.1        23978
2012-06-29 13:45:00 253.0 253.4 253.0 253.4    451      247.3      253.4     246.9       253.4        52539

There are duplicated results using the subset, how do I achieve only the first record of the day? I would then be able to plot the count of records for periods in the day.

Also, are there alternate methods to get the results I want? Thanks in advance.

Edit:

Sample output should look like this, count could either be 1st result for day or aggregated (more than 1 occurrence in that day):

Time        Count
08:40:00    60
08:45:00    54
08:50:00    60
...
14:00:00    20
14:05:00    12
14:10:00    30

Answer 1

You can get the first observation of each day via:

y <- apply.daily(x, first)

Then you can simply aggregate the count based on hours and minutes:

z <- aggregate(1:NROW(y), by=list(Time=format(index(y),"%H:%M")), sum)