excel - record how long a variable was above a level in r -

i working on converting project have programmed in excel r. reason doing code includes lots of logic , data means thats excel's performance poor. far have coded around 50% of project in r , extremely impressed performance.

the code have following:

1. loads 5min time-series data of stock , adds day of year column labeled doy in example below.

the ohlc data looks this:

       date               open        high       low         close      doy 1   2015-09-21 09:30:00 164.6700    164.7100    164.3700    164.5300    264 2   2015-09-21 09:35:00 164.5300    164.9000    164.5300    164.6400    264 3   2015-09-21 09:40:00 164.6600    164.8900    164.6000    164.8900    264 4   2015-09-21 09:45:00 164.9100    165.0900    164.9100    164.9736    264 5   2015-09-21 09:50:00 164.9399    165.0980    164.8200    164.8200    264 

2. converts data table called df df <- tbl_df(dia_5)
3. using plyr hint of ttr filters through data creating set of 10 new variables in new data frame called data. see below:

 data <- structure(list(doy = c(264, 265, 266, 267, 268, 271, 272, 11,12, 13),   date = structure(c(1442824200, 1442910600, 1442997000,1443083400,   1443169800, 1443429000, 1443515400, 1452504600,   1452591000,1452677400), class = c("posixct", "posixt"), tzone = ""), or_high = c(164.71,162.96, 163.38, 161.37, 163.91, 162.06, 160.22,  164.5, 165.23,165.84), or_low = c(164.37, 162.62, 162.98, 161.06,  163.57, 161.66,159.7, 164.06, 164.84, 165.4), hod = c(165.56, 163.36,  163.38,162.24, 164.43, 162.06, 160.96, 164.5, 165.78, 165.84), lod =  c(165.22,163.1, 162.98, 161.95, 164.24, 161.66, 160.75, 164.06,  165.56,165.4), close = c(164.92, 163.02, 162.58, 161.85, 162.94,  159.84,160.19, 163.83, 165.02, 161.38), range =  c(0.340000000000003,0.260000000000019, 0.400000000000006,  0.29000000000002, 0.189999999999998,0.400000000000006,  0.210000000000008, 0.439999999999998, 0.219999999999999,0.439999999999998), `a-val` = c(na, na, na, na, na, na, na,  0.0673439999999994,0.0659639999999996, 0.0729499999999996), `a-up` = c(na, na, na,na, na, na, na, 164.567344, 165.295964,  165.91295), `a-down` = c(na,na, na, na, na, na, na, 163.992656,  164.774036, 165.32705)), .names = c("doy","date", "or_high", "or_low",  "hod", "lod", "close", "range","a-val", "a-up", "a-down"),  row.names = c(1l, 2l, 3l, 4l, 5l,6l, 7l, 78l, 79l, 80l), class = "data.frame")  

the next part gets complicated. need analyse high , low prices of each 5 minute bar of day in relation a-up & a-down , close values seen in table. looking able compute score day depending on time spent above a-up level or below a-down level.

the way got in excel index each 5 minute high & low price of time series used logic score activity in 5min time slice. if low > a-up level given 1 , - 1 if high < a-down. scoring if price stays > a-up level or < a-down level greater 30 mins score 2 0r -2. achieved using running 5 period sum of results of , if 1 had more 5 ones knew price had stayed > a-up level etc score 2.

for days scoring need know following;

1. did price stay above or below , level > 30 minutes or fail spending < 30 minutes there?
2. if price went above , below both levels in 1 day, level did break first?

so after long winded intro question. out there have idea of best way go coding this. don't need specific code packages may accomplish this. mentioned above reason switching r speed whatever code used must efficient. when have coded intend on programming loop can analyse several hundred instruments.

thanks.