r - How to aggregate data.table by applying two functions -

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• count number of rows in data frame in r based on group [duplicate] 8 answers

i have data.table lists user id, week number, fact user did (processed, either 0 or 1) , column use count how many values have, called howmany:

 data <- data.table(weeknumber=c(33,33,33,34,34,33,33,34,34),           user=c(1,1,1,1,1,2,2,2,2),           processed=c(1,1,0,0,1,0,1,0,1),          howmany=c(1,1,1,1,1,1,1,1,1)) 

i want find, each week, sum of things done , not done, this:

> dcast(setdt(data), weeknumber~processed, value.var="howmany", sum)     weeknumber 0 1 1:         33 2 3 2:         34 2 2 

now i'd find average number of things done , not done week, in case have aggregate user before, fail @ step:

> dcast(setdt(data), weeknumber~processed+user, value.var="howmany", mean)    weeknumber 0_1 0_2 1_1 1_2 1:        33   1   1   1   1 2:        34   1   1   1   1 

while optimal results be:

weeknumber 0   1         33 1 1.5         34 1   1 

what this:

dat[, user_processed := paste(user, processed, sep="_")] dcast(dat, weeknumber~user_processed, value.var="processed", length)  

which gives you:

   weeknumber 10001041_1 10001042_0 10001042_1 1:         33          0          3          2 2:         43          5          0          0 

sample data used:

dat <- fread("user processed weeknumber   1: 10001042         0         33       2: 10001042         0         33       3: 10001042         1         33       4: 10001042         0         33       5: 10001042         1         33       870: 10001041         1         43       871: 10001041         1         43       872: 10001041         1         43       873: 10001041         1         43       874: 10001041         1         43")  dat <- dat[, v1 := null] setnames(dat, c("user", "processed", "weeknumber"))