zuzana zajkova
2013-Apr-29 10:44 UTC
[R] Counting number of consecutive occurrences per rows
Hi, I would appreciate if somebody could help me with following calculation. I have a dataframe, by 10 minutes time, for mostly one year data. This is small example:> dput(test)structure(list(jul = structure(c(14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655), origin = structure(0, class = "Date")), time = structure(c(1266258354, 1266258954, 1266259554, 1266260154, 1266260754, 1266261354, 1266261954, 1266262554, 1266263154, 1266263754, 1266264354, 1266264954, 1266265554, 1266266154, 1266266754, 1266267354), class = c("POSIXct", "POSIXt"), tzone "GMT"), act = c(130, 23, 45, 200, 200, 200, 199, 150, 0, 0, 0, 0, 34, 200, 200, 145), day = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0)), .Names = c("jul", "time", "act", "day" ), class = "data.frame", row.names = c(510L, 512L, 514L, 516L, 518L, 520L, 522L, 524L, 526L, 528L, 530L, 532L, 534L, 536L, 538L, 540L)) Looks like this:> testjul time act day 510 14655 2010-02-15 18:25:54 130 1 512 14655 2010-02-15 18:35:54 23 1 514 14655 2010-02-15 18:45:54 45 1 516 14655 2010-02-15 18:55:54 200 1 518 14655 2010-02-15 19:05:54 200 1 520 14655 2010-02-15 19:15:54 200 1 522 14655 2010-02-15 19:25:54 199 1 524 14655 2010-02-15 19:35:54 150 1 526 14655 2010-02-15 19:45:54 0 1 528 14655 2010-02-15 19:55:54 0 1 530 14655 2010-02-15 20:05:54 0 0 532 14655 2010-02-15 20:15:54 0 0 534 14655 2010-02-15 20:25:54 34 0 536 14655 2010-02-15 20:35:54 200 0 538 14655 2010-02-15 20:45:54 200 0 540 14655 2010-02-15 20:55:54 145 0 What I would like to calculate is the number of consecutive occurrences of values 200, 0 and together values from 1 til 199 (in fact the values that differ from 200 and 0) in column "act". I would like to get something like this (result$res)> resultjul time act day res res2 510 14655 2010-02-15 18:25:54 130 1 3 3 512 14655 2010-02-15 18:35:54 23 1 3 3 514 14655 2010-02-15 18:45:54 45 1 3 3 516 14655 2010-02-15 18:55:54 200 1 3 3 518 14655 2010-02-15 19:05:54 200 1 3 3 520 14655 2010-02-15 19:15:54 200 1 3 3 522 14655 2010-02-15 19:25:54 199 1 2 2 524 14655 2010-02-15 19:35:54 150 1 2 2 526 14655 2010-02-15 19:45:54 0 1 4 2 528 14655 2010-02-15 19:55:54 0 1 4 2 530 14655 2010-02-15 20:05:54 0 0 4 2 532 14655 2010-02-15 20:15:54 0 0 4 2 534 14655 2010-02-15 20:25:54 34 0 1 1 536 14655 2010-02-15 20:35:54 200 0 2 2 538 14655 2010-02-15 20:45:54 200 0 2 2 540 14655 2010-02-15 20:55:54 145 0 1 1 And if possible, distinguish among day==1 and day==0 (see the "act" values of 0 for example), results as in result$res2. After it I would like to make a resume table per days (jul): where maxres is max(result$res) for the "act" value where minres is min(result$res) for the "act" value where sumres is sum(result$res) for the "act" value (for example, if the 200 value ocurrs in different times per day(jul) consecutively 3, 5, 1, 6 and 7 times the sumres would be 3+5+1+6+7= 22) something like this (this are made up numbers): jul act maxres minres sumres 14655 0 4 1 25 14655 200 3 2 48 14655 1-199 3 1 71 14656 0 8 2 38 14656 200 15 3 60 14656 1-199 11 4 46 ... (theoretically the sum of sumres per day(jul) should be 144) ____________> sessionInfo()R version 2.15.2 (2012-10-26) Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) ____________ I hope my explanation is sufficient. I appreciate any hint. Thank you, Zuzana [[alternative HTML version deleted]]
try this:> test <- structure(list(jul = structure(c(14655, 14655, 14655, 14655,+ 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, + 14655, 14655, 14655), origin = structure(0, class = "Date")), + time = structure(c(1266258354, 1266258954, 1266259554, 1266260154, + 1266260754, 1266261354, 1266261954, 1266262554, 1266263154, + 1266263754, 1266264354, 1266264954, 1266265554, 1266266154, + 1266266754, 1266267354), class = c("POSIXct", "POSIXt"), tzone + "GMT"), + act = c(130, 23, 45, 200, 200, 200, 199, 150, 0, 0, 0, 0, + 34, 200, 200, 145), day = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, + 0, 0, 0, 0, 0, 0)), .Names = c("jul", "time", "act", "day" + ), class = "data.frame", row.names = c(510L, 512L, 514L, 516L, + 518L, 520L, 522L, 524L, 526L, 528L, 530L, 532L, 534L, 536L, 538L, + 540L))> > # add key to separate data > test$key <- ifelse(test$act == 0+ , 1L # 0 + , ifelse(test$act == 200 + , 3L # 200 + , 2L # 1-199 + ) + )> # mark changes in sequence > test$resChange <- cumsum(c(1L, abs(diff(test$key)))) > test$res <- ave(test$resChange, test$resChange, FUN = length) > > test$res2 <- ave(test$resChange, test$resChange, test$day, FUN = length) > > testjul time act day key resChange res res2 510 14655 2010-02-15 18:25:54 130 1 2 1 3 3 512 14655 2010-02-15 18:35:54 23 1 2 1 3 3 514 14655 2010-02-15 18:45:54 45 1 2 1 3 3 516 14655 2010-02-15 18:55:54 200 1 3 2 3 3 518 14655 2010-02-15 19:05:54 200 1 3 2 3 3 520 14655 2010-02-15 19:15:54 200 1 3 2 3 3 522 14655 2010-02-15 19:25:54 199 1 2 3 2 2 524 14655 2010-02-15 19:35:54 150 1 2 3 2 2 526 14655 2010-02-15 19:45:54 0 1 1 4 4 2 528 14655 2010-02-15 19:55:54 0 1 1 4 4 2 530 14655 2010-02-15 20:05:54 0 0 1 4 4 2 532 14655 2010-02-15 20:15:54 0 0 1 4 4 2 534 14655 2010-02-15 20:25:54 34 0 2 5 1 1 536 14655 2010-02-15 20:35:54 200 0 3 6 2 2 538 14655 2010-02-15 20:45:54 200 0 3 6 2 2 540 14655 2010-02-15 20:55:54 145 0 2 7 1 1>On Mon, Apr 29, 2013 at 6:44 AM, zuzana zajkova <zuzulaz@gmail.com> wrote:> Hi, > > I would appreciate if somebody could help me with following calculation. > I have a dataframe, by 10 minutes time, for mostly one year data. This is > small example: > > > dput(test) > structure(list(jul = structure(c(14655, 14655, 14655, 14655, > 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, > 14655, 14655, 14655), origin = structure(0, class = "Date")), > time = structure(c(1266258354, 1266258954, 1266259554, 1266260154, > 1266260754, 1266261354, 1266261954, 1266262554, 1266263154, > 1266263754, 1266264354, 1266264954, 1266265554, 1266266154, > 1266266754, 1266267354), class = c("POSIXct", "POSIXt"), tzone > "GMT"), > act = c(130, 23, 45, 200, 200, 200, 199, 150, 0, 0, 0, 0, > 34, 200, 200, 145), day = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, > 0, 0, 0, 0, 0, 0)), .Names = c("jul", "time", "act", "day" > ), class = "data.frame", row.names = c(510L, 512L, 514L, 516L, > 518L, 520L, 522L, 524L, 526L, 528L, 530L, 532L, 534L, 536L, 538L, > 540L)) > > Looks like this: > > > test > jul time act day > 510 14655 2010-02-15 18:25:54 130 1 > 512 14655 2010-02-15 18:35:54 23 1 > 514 14655 2010-02-15 18:45:54 45 1 > 516 14655 2010-02-15 18:55:54 200 1 > 518 14655 2010-02-15 19:05:54 200 1 > 520 14655 2010-02-15 19:15:54 200 1 > 522 14655 2010-02-15 19:25:54 199 1 > 524 14655 2010-02-15 19:35:54 150 1 > 526 14655 2010-02-15 19:45:54 0 1 > 528 14655 2010-02-15 19:55:54 0 1 > 530 14655 2010-02-15 20:05:54 0 0 > 532 14655 2010-02-15 20:15:54 0 0 > 534 14655 2010-02-15 20:25:54 34 0 > 536 14655 2010-02-15 20:35:54 200 0 > 538 14655 2010-02-15 20:45:54 200 0 > 540 14655 2010-02-15 20:55:54 145 0 > > > What I would like to calculate is the number of consecutive occurrences of > values 200, 0 and together values from 1 til 199 (in fact the values that > differ from 200 and 0) in column "act". > > I would like to get something like this (result$res) > > > result > jul time act day res res2 > 510 14655 2010-02-15 18:25:54 130 1 3 3 > 512 14655 2010-02-15 18:35:54 23 1 3 3 > 514 14655 2010-02-15 18:45:54 45 1 3 3 > 516 14655 2010-02-15 18:55:54 200 1 3 3 > 518 14655 2010-02-15 19:05:54 200 1 3 3 > 520 14655 2010-02-15 19:15:54 200 1 3 3 > 522 14655 2010-02-15 19:25:54 199 1 2 2 > 524 14655 2010-02-15 19:35:54 150 1 2 2 > 526 14655 2010-02-15 19:45:54 0 1 4 2 > 528 14655 2010-02-15 19:55:54 0 1 4 2 > 530 14655 2010-02-15 20:05:54 0 0 4 2 > 532 14655 2010-02-15 20:15:54 0 0 4 2 > 534 14655 2010-02-15 20:25:54 34 0 1 1 > 536 14655 2010-02-15 20:35:54 200 0 2 2 > 538 14655 2010-02-15 20:45:54 200 0 2 2 > 540 14655 2010-02-15 20:55:54 145 0 1 1 > > And if possible, distinguish among day==1 and day==0 (see the "act" values > of 0 for example), results as in result$res2. > > After it I would like to make a resume table per days (jul): > where maxres is max(result$res) for the "act" value > where minres is min(result$res) for the "act" value > where sumres is sum(result$res) for the "act" value (for example, if the > 200 value ocurrs in different times per day(jul) consecutively 3, 5, 1, 6 > and 7 times the sumres would be 3+5+1+6+7= 22) > > something like this (this are made up numbers): > > jul act maxres minres sumres > 14655 0 4 1 25 > 14655 200 3 2 48 > 14655 1-199 3 1 71 > 14656 0 8 2 38 > 14656 200 15 3 60 > 14656 1-199 11 4 46 > ... > (theoretically the sum of sumres per day(jul) should be 144) > > ____________ > > sessionInfo() > R version 2.15.2 (2012-10-26) > Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) > ____________ > > I hope my explanation is sufficient. I appreciate any hint. > Thank you, > > Zuzana > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- Jim Holtman Data Munger Guru What is the problem that you are trying to solve? Tell me what you want to do, not how you want to do it. [[alternative HTML version deleted]]
Forgot the last part of the question:> test <- structure(list(jul = structure(c(14655, 14655, 14655, 14655,+ 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, + 14655, 14655, 14655), origin = structure(0, class = "Date")), + time = structure(c(1266258354, 1266258954, 1266259554, 1266260154, + 1266260754, 1266261354, 1266261954, 1266262554, 1266263154, + 1266263754, 1266264354, 1266264954, 1266265554, 1266266154, + 1266266754, 1266267354), class = c("POSIXct", "POSIXt"), tzone + "GMT"), + act = c(130, 23, 45, 200, 200, 200, 199, 150, 0, 0, 0, 0, + 34, 200, 200, 145), day = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, + 0, 0, 0, 0, 0, 0)), .Names = c("jul", "time", "act", "day" + ), class = "data.frame", row.names = c(510L, 512L, 514L, 516L, + 518L, 520L, 522L, 524L, 526L, 528L, 530L, 532L, 534L, 536L, 538L, + 540L))> > # add key to separate data > test$key <- ifelse(test$act == 0+ , 1L # 0 + , ifelse(test$act == 200 + , 3L # 200 + , 2L # 1-199 + ) + )> # mark changes in sequence > test$resChange <- cumsum(c(1L, abs(diff(test$key)))) > test$res <- ave(test$resChange, test$resChange, FUN = length) > > test$res2 <- ave(test$resChange, test$resChange, test$day, FUN = length) > > require(data.table) # use this for aggregation > test <- data.table(test) > testResume <- test[+ , list(maxres = max(res) + , minres = min(res) + , sumres = length(unique(resChange)) + ) + , keyby = c('day', 'key') + ]> # change 'key' > testResume$key <- c('0', '1-199', '200')[testResume$key] > testResumeday key maxres minres sumres 1: 0 0 4 4 1 2: 0 1-199 1 1 2 3: 0 200 2 2 1 4: 1 0 4 4 1 5: 1 1-199 3 2 2 6: 1 200 3 3 1>On Mon, Apr 29, 2013 at 6:44 AM, zuzana zajkova <zuzulaz@gmail.com> wrote:> Hi, > > I would appreciate if somebody could help me with following calculation. > I have a dataframe, by 10 minutes time, for mostly one year data. This is > small example: > > > dput(test) > structure(list(jul = structure(c(14655, 14655, 14655, 14655, > 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, > 14655, 14655, 14655), origin = structure(0, class = "Date")), > time = structure(c(1266258354, 1266258954, 1266259554, 1266260154, > 1266260754, 1266261354, 1266261954, 1266262554, 1266263154, > 1266263754, 1266264354, 1266264954, 1266265554, 1266266154, > 1266266754, 1266267354), class = c("POSIXct", "POSIXt"), tzone > "GMT"), > act = c(130, 23, 45, 200, 200, 200, 199, 150, 0, 0, 0, 0, > 34, 200, 200, 145), day = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, > 0, 0, 0, 0, 0, 0)), .Names = c("jul", "time", "act", "day" > ), class = "data.frame", row.names = c(510L, 512L, 514L, 516L, > 518L, 520L, 522L, 524L, 526L, 528L, 530L, 532L, 534L, 536L, 538L, > 540L)) > > Looks like this: > > > test > jul time act day > 510 14655 2010-02-15 18:25:54 130 1 > 512 14655 2010-02-15 18:35:54 23 1 > 514 14655 2010-02-15 18:45:54 45 1 > 516 14655 2010-02-15 18:55:54 200 1 > 518 14655 2010-02-15 19:05:54 200 1 > 520 14655 2010-02-15 19:15:54 200 1 > 522 14655 2010-02-15 19:25:54 199 1 > 524 14655 2010-02-15 19:35:54 150 1 > 526 14655 2010-02-15 19:45:54 0 1 > 528 14655 2010-02-15 19:55:54 0 1 > 530 14655 2010-02-15 20:05:54 0 0 > 532 14655 2010-02-15 20:15:54 0 0 > 534 14655 2010-02-15 20:25:54 34 0 > 536 14655 2010-02-15 20:35:54 200 0 > 538 14655 2010-02-15 20:45:54 200 0 > 540 14655 2010-02-15 20:55:54 145 0 > > > What I would like to calculate is the number of consecutive occurrences of > values 200, 0 and together values from 1 til 199 (in fact the values that > differ from 200 and 0) in column "act". > > I would like to get something like this (result$res) > > > result > jul time act day res res2 > 510 14655 2010-02-15 18:25:54 130 1 3 3 > 512 14655 2010-02-15 18:35:54 23 1 3 3 > 514 14655 2010-02-15 18:45:54 45 1 3 3 > 516 14655 2010-02-15 18:55:54 200 1 3 3 > 518 14655 2010-02-15 19:05:54 200 1 3 3 > 520 14655 2010-02-15 19:15:54 200 1 3 3 > 522 14655 2010-02-15 19:25:54 199 1 2 2 > 524 14655 2010-02-15 19:35:54 150 1 2 2 > 526 14655 2010-02-15 19:45:54 0 1 4 2 > 528 14655 2010-02-15 19:55:54 0 1 4 2 > 530 14655 2010-02-15 20:05:54 0 0 4 2 > 532 14655 2010-02-15 20:15:54 0 0 4 2 > 534 14655 2010-02-15 20:25:54 34 0 1 1 > 536 14655 2010-02-15 20:35:54 200 0 2 2 > 538 14655 2010-02-15 20:45:54 200 0 2 2 > 540 14655 2010-02-15 20:55:54 145 0 1 1 > > And if possible, distinguish among day==1 and day==0 (see the "act" values > of 0 for example), results as in result$res2. > > After it I would like to make a resume table per days (jul): > where maxres is max(result$res) for the "act" value > where minres is min(result$res) for the "act" value > where sumres is sum(result$res) for the "act" value (for example, if the > 200 value ocurrs in different times per day(jul) consecutively 3, 5, 1, 6 > and 7 times the sumres would be 3+5+1+6+7= 22) > > something like this (this are made up numbers): > > jul act maxres minres sumres > 14655 0 4 1 25 > 14655 200 3 2 48 > 14655 1-199 3 1 71 > 14656 0 8 2 38 > 14656 200 15 3 60 > 14656 1-199 11 4 46 > ... > (theoretically the sum of sumres per day(jul) should be 144) > > ____________ > > sessionInfo() > R version 2.15.2 (2012-10-26) > Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) > ____________ > > I hope my explanation is sufficient. I appreciate any hint. > Thank you, > > Zuzana > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- Jim Holtman Data Munger Guru What is the problem that you are trying to solve? Tell me what you want to do, not how you want to do it. [[alternative HTML version deleted]]
Hi rrr<-rle(as.numeric(cut(test$act, c(0,1,199,200), include.lowest=T))) test$res <- rep(rrr$lengths, rrr$lengths) If you put it in function fff<- function(x, limits=c(0,1,199,200)) { rrr<-rle(as.numeric(cut(x, limits, include.lowest=T))) res <- rep(rrr$lengths, rrr$lengths) res } you can use split/lapply approach test$res2<-unlist(lapply(split(test$act, factor(test$day, levels=c(1,0))), fff)) Beware of correct ordering of days in output. Without correct leveling of factor 0 precedes 1. And for the last part probably aggregate can be the way.> aggregate(test$res, list(test$jul, cut(test$act, c(0,1,199,200), include.lowest=T)), max)Group.1 Group.2 x 1 14655 [0,1] 4 2 14655 (1,199] 3 3 14655 (199,200] 3> aggregate(test$res, list(test$jul, cut(test$act, c(0,1,199,200), include.lowest=T)), min)Group.1 Group.2 x 1 14655 [0,1] 4 2 14655 (1,199] 1 3 14655 (199,200] 2 Regards Petr> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- > project.org] On Behalf Of zuzana zajkova > Sent: Monday, April 29, 2013 12:45 PM > To: r-help at r-project.org > Subject: [R] Counting number of consecutive occurrences per rows > > Hi, > > I would appreciate if somebody could help me with following > calculation. > I have a dataframe, by 10 minutes time, for mostly one year data. This > is small example: > > > dput(test) > structure(list(jul = structure(c(14655, 14655, 14655, 14655, 14655, > 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, > 14655), origin = structure(0, class = "Date")), > time = structure(c(1266258354, 1266258954, 1266259554, 1266260154, > 1266260754, 1266261354, 1266261954, 1266262554, 1266263154, > 1266263754, 1266264354, 1266264954, 1266265554, 1266266154, > 1266266754, 1266267354), class = c("POSIXct", "POSIXt"), tzone > "GMT"), > act = c(130, 23, 45, 200, 200, 200, 199, 150, 0, 0, 0, 0, > 34, 200, 200, 145), day = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, > 0, 0, 0, 0, 0, 0)), .Names = c("jul", "time", "act", "day" > ), class = "data.frame", row.names = c(510L, 512L, 514L, 516L, 518L, > 520L, 522L, 524L, 526L, 528L, 530L, 532L, 534L, 536L, 538L, > 540L)) > > Looks like this: > > > test > jul time act day > 510 14655 2010-02-15 18:25:54 130 1 > 512 14655 2010-02-15 18:35:54 23 1 > 514 14655 2010-02-15 18:45:54 45 1 > 516 14655 2010-02-15 18:55:54 200 1 > 518 14655 2010-02-15 19:05:54 200 1 > 520 14655 2010-02-15 19:15:54 200 1 > 522 14655 2010-02-15 19:25:54 199 1 > 524 14655 2010-02-15 19:35:54 150 1 > 526 14655 2010-02-15 19:45:54 0 1 > 528 14655 2010-02-15 19:55:54 0 1 > 530 14655 2010-02-15 20:05:54 0 0 > 532 14655 2010-02-15 20:15:54 0 0 > 534 14655 2010-02-15 20:25:54 34 0 > 536 14655 2010-02-15 20:35:54 200 0 > 538 14655 2010-02-15 20:45:54 200 0 > 540 14655 2010-02-15 20:55:54 145 0 > > > What I would like to calculate is the number of consecutive occurrences > of values 200, 0 and together values from 1 til 199 (in fact the > values that differ from 200 and 0) in column "act". > > I would like to get something like this (result$res) > > > result > jul time act day res res2 > 510 14655 2010-02-15 18:25:54 130 1 3 3 > 512 14655 2010-02-15 18:35:54 23 1 3 3 > 514 14655 2010-02-15 18:45:54 45 1 3 3 > 516 14655 2010-02-15 18:55:54 200 1 3 3 > 518 14655 2010-02-15 19:05:54 200 1 3 3 > 520 14655 2010-02-15 19:15:54 200 1 3 3 > 522 14655 2010-02-15 19:25:54 199 1 2 2 > 524 14655 2010-02-15 19:35:54 150 1 2 2 > 526 14655 2010-02-15 19:45:54 0 1 4 2 > 528 14655 2010-02-15 19:55:54 0 1 4 2 > 530 14655 2010-02-15 20:05:54 0 0 4 2 > 532 14655 2010-02-15 20:15:54 0 0 4 2 > 534 14655 2010-02-15 20:25:54 34 0 1 1 > 536 14655 2010-02-15 20:35:54 200 0 2 2 > 538 14655 2010-02-15 20:45:54 200 0 2 2 > 540 14655 2010-02-15 20:55:54 145 0 1 1 > > And if possible, distinguish among day==1 and day==0 (see the "act" > values of 0 for example), results as in result$res2. > > After it I would like to make a resume table per days (jul): > where maxres is max(result$res) for the "act" value where minres is > min(result$res) for the "act" value where sumres is sum(result$res) for > the "act" value (for example, if the 200 value ocurrs in different > times per day(jul) consecutively 3, 5, 1, 6 and 7 times the sumres > would be 3+5+1+6+7= 22) > > something like this (this are made up numbers): > > jul act maxres minres sumres > 14655 0 4 1 25 > 14655 200 3 2 48 > 14655 1-199 3 1 71 > 14656 0 8 2 38 > 14656 200 15 3 60 > 14656 1-199 11 4 46 > ... > (theoretically the sum of sumres per day(jul) should be 144) > > ____________ > > sessionInfo() > R version 2.15.2 (2012-10-26) > Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) ____________ > > I hope my explanation is sufficient. I appreciate any hint. > Thank you, > > Zuzana > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code.