Converting this ugly for-loop to something more R-friendly

Question

Been using SO as a resource constantly for my work. Thanks for holding together such a great community.

I'm trying to do something kinda complex, and the only way I can think to do it right now is with a pair of nested for-loops (I know that's frowned upon in R)... I have records of three million-odd course enrollments: student UserID's paired with CourseID's. In each row, there's a bunch of data including start/end dates and scores and so forth. What I need to do is, for each enrollment, calculate the average score for that user across the courses she's taken before the course in the enrollment.

The code I'm using for the for-loop follows:

data$Mean.Prior.Score <- 0
for (i in as.numeric(rownames(data)) {
    sum <- 0
    count <- 0
    for (j in as.numeric(rownames(data[data$UserID == data$UserID[i],]))) {
            if (data$Course.End.Date[j] < data$Course.Start.Date[i]) {
                sum <- sum + data$Score[j]
                count <- count + 1
            }
    }
if (count != 0)
    data$Mean.Prior.Score[i] <- sum / count
}

I'm pretty sure this would work, but it runs incredibly slowly... my data frame has over three million rows, but after a good 10 minutes of chugging, the outer loop has only run through 850 of the records. That seems way slower than the time complexity would suggest, especially given that each user has only 5 or 6 courses to her name on average.

Oh, and I should mention that I converted the date strings with as.POSIXct() before running the loop, so the date comparison step shouldn't be too terribly slow...

There's got to be a better way to do this... any suggestions?

---

Edit: As per mnel's request... finally got dput to play nicely. Had to add control = NULL. Here 'tis:

structure(list(Username = structure(1:20, .Label = c("100225", 
"100226", "100228", "1013170", "102876", "105796", "106753", 
"106755", "108568", "109038", "110150", "110200", "110350", "111873", 
"111935", "113579", "113670", "117562", "117869", "118329"), class = "factor"), 
User.ID = c(2313737L, 2314278L, 2314920L, 9708829L, 2325896L, 
2315617L, 2314644L, 2314977L, 2330148L, 2315081L, 2314145L, 
2316213L, 2317734L, 2314363L, 2361187L, 2315374L, 2314250L, 
2361507L, 2325592L, 2360182L), Course.ID = c(2106468L, 2106578L, 
2106493L, 5426406L, 2115455L, 2107320L, 2110286L, 2110101L, 
2118574L, 2106876L, 2110108L, 2110058L, 2109958L, 2108222L, 
2127976L, 2106638L, 2107020L, 2127451L, 2117022L, 2126506L
), Course = structure(c(1L, 7L, 10L, 15L, 11L, 19L, 4L, 6L, 
3L, 12L, 2L, 9L, 17L, 8L, 20L, 18L, 13L, 16L, 5L, 14L), .Label = c("ACCT212_A", 
"BIOS200_N", "BIS220_T", "BUSN115_A", "BUSN115_T", "CARD205_A", 
"CIS211_A", "CIS275_X", "CIS438_S", "ENGL112_A", "ENGL112_B", 
"ENGL227_K", "GM400_A", "GM410_A", "HUMN232_M", "HUMN432_W", 
"HUMN445_A", "MATH100_X", "MM575_A", "PSYC110_Y"), class = "factor"), 
Course.Start.Date = structure(c(1098662400, 1098662400, 1098662400, 
1309737600, 1099267200, 1098662400, 1099267200, 1099267200, 
1098662400, 1098662400, 1099267200, 1099267200, 1099267200, 
1098662400, 1104105600, 1098662400, 1098662400, 1104105600, 
1098662400, 1104105600), class = c("POSIXct", "POSIXt"), tzone = "GMT"), 
Term.ID = c(12056L, 12056L, 12056L, 66282L, 12057L, 12056L, 
12057L, 12057L, 12056L, 12056L, 12057L, 12057L, 12057L, 12056L, 
13469L, 12056L, 12056L, 13469L, 12056L, 13469L), Term.Name = structure(c(2L, 
2L, 2L, 4L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 3L, 2L, 
2L, 3L, 2L, 3L), .Label = c("Fall 2004", "Fall 2004 Session A", 
"Fall 2004 Session B", "Summer Session A 2011"), class = "factor"), 
Term.Start.Date = structure(c(1L, 1L, 1L, 4L, 2L, 1L, 2L, 
2L, 1L, 1L, 2L, 2L, 2L, 1L, 3L, 1L, 1L, 3L, 1L, 3L), .Label = c("2004-10-21", 
"2004-10-28", "2004-12-27", "2011-06-26"), class = "factor"), 
Score = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.125, 
0, 0, 0, 0, 0), First.Course.Date = structure(c(1L, 1L, 1L, 
4L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 3L, 1L, 1L, 3L, 
1L, 3L), .Label = c("2004-10-25", "2004-11-01", "2004-12-27", 
"2011-07-04"), class = "factor"), First.Term.Date = structure(c(1L, 
1L, 1L, 4L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 3L, 1L, 
1L, 3L, 1L, 3L), .Label = c("2004-10-21", "2004-10-28", "2004-12-27", 
"2011-06-26"), class = "factor"), First.Timer = c(TRUE, TRUE, 
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE), Course.Code = structure(c(1L, 
6L, 9L, 13L, 9L, 17L, 4L, 5L, 3L, 10L, 2L, 8L, 15L, 7L, 18L, 
16L, 11L, 14L, 4L, 12L), .Label = c("ACCT212", "BIOS200", 
"BIS220", "BUSN115", "CARD205", "CIS211", "CIS275", "CIS438", 
"ENGL112", "ENGL227", "GM400", "GM410", "HUMN232", "HUMN432", 
"HUMN445", "MATH100", "MM575", "PSYC110"), class = "factor"), 
Course.End.Date = structure(c(1L, 1L, 1L, 4L, 2L, 1L, 2L, 
2L, 1L, 1L, 2L, 2L, 2L, 1L, 3L, 1L, 1L, 3L, 1L, 3L), .Label = c("2004-12-19", 
"2005-02-27", "2005-03-26", "2011-08-28"), class = "factor")), .Names = c("Username", 
"User.ID", "Course.ID", "Course", "Course.Start.Date", "Term.ID", 
"Term.Name", "Term.Start.Date", "Score", "First.Course.Date", 
"First.Term.Date", "First.Timer", "Course.Code", "Course.End.Date"
), row.names = c(NA, 20L), class = "data.frame")

Answer 1

I found that data.table worked well.

# Create some data.
library(data.table)
set.seed(1)
n=3e6
numCourses=5 # Average courses per student
data=data.table(UserID=as.character(round(runif(n,1,round(n/numCourses)))),course=1:n,Score=runif(n),CourseStartDate=as.Date('2000-01-01')+round(runif(n,1,365)))
data$CourseEndDate=data$CourseStartDate+round(runif(n,1,100))
setkey(data,UserID)
# test=function(CourseEndDate,Score,CourseStartDate) sapply(CourseStartDate, function(y) mean(Score[y>CourseEndDate]))
# I vastly reduced the number of comparisons with a better "test" function.
test2=function(CourseEndDate,Score,CourseStartDate) {
    o.end = order(CourseEndDate)
    run.avg = cumsum(Score[o.end])/seq_along(CourseEndDate)
    idx=findInterval(CourseStartDate,CourseEndDate[o.end])
    idx=ifelse(idx==0,NA,idx)
    run.avg[idx]
}
system.time(data$MeanPriorScore<-data[,test2(CourseEndDate,Score,CourseStartDate),by=UserID]$V1) 
#  For three million courses, at an average of 5 courses per student:
#    user  system elapsed 
#    122.06    0.22  122.45 

---

Running a test to see if it looks the same as your code:

set.seed(1)
n=1e2
data=data.table(UserID=as.character(round(runif(n,1,1000))),course=1:n,Score=runif(n),CourseStartDate=as.Date('2000-01-01')+round(runif(n,1,365)))
data$CourseEndDate=data$CourseStartDate+round(runif(n,1,100))
setkey(data,UserID)
data$MeanPriorScore<-data[,test2(CourseEndDate,Score,CourseStartDate),by=UserID]$V1
data["246"]
#   UserID course     Score CourseStartDate CourseEndDate MeanPriorScore
#1:    246     54 0.4531314      2000-08-09    2000-09-20      0.9437248
#2:    246     89 0.9437248      2000-02-19    2000-03-02             NA

# A comparison with your for loop (slightly modified)
data$MeanPriorScore.old<-NA # Set to NaN instead of zero for easy comparison.
# I think you forgot a bracket here. Also, There is no need to work with the rownames.
for (i in seq(nrow(data))) { 
    sum <- 0
    count <- 0
    # I reduced the complexity of figuring out the vector to loop through.
    # It will result in the exact same thing if there are no rownames.
    for (j in which(data$UserID == data$UserID[i])) {
            if (data$CourseEndDate[j] <= data$CourseStartDate[i]) {
                sum <- sum + data$Score[j]
                count <- count + 1
            }
    }
    # I had to add "[i]" here. I think that is what you meant.
    if (count != 0) data$MeanPriorScore.old[i] <- sum / count 
}
identical(data$MeanPriorScore,data$MeanPriorScore.old)
# [1] TRUE

Answer 2

This seems to be what you want

library(data.table) 
# create a data.table object
DT <- data.table(data)
# key by userID 
setkeyv(DT, 'userID')

# for each userID, where the Course.End.Date < Course.Start.Date
# return the mean score

# This is too simplistic
# DT[Course.End.Date < Course.Start.Date,
#   list(Mean.Prior.Score = mean(Score)) , 
#   by = list(userID)]

As per @jorans comment, this will be more complex than the code above.