This is a quick trial of adding overall and conditional (by user) average columns in a data frame. base,plyr,dplyr,data.table,dplyr + data.table packages are used. Personally I perfer dplyr + data.table - dplyr for comperhensive syntax and data.table for speed.

 1## set up variables
 2size <- 36000
 3numUsers <- 4900
 4# roughly each user has 7 sessions
 5numSessions <- (numUsers / 7) - ((numUsers / 7) %% 1)
 6 
 7## create data frame
 8set.seed(123457)
 9userIds <- sample.int(numUsers, size=size, replace=TRUE)
10ssIds <- sample.int(numSessions, size=size, replace=TRUE)
11scores <- sample.int(10, size=size, replace=TRUE) 
12
13preDf <- data.frame(User=userIds, Session=ssIds, Score=scores)
14preDf$User <- as.factor(preDf$User)

Adding overall average

As calculating overall average is not complicated, I don’t find a big difference among packages.

1# base
2system.time(overallDf1 <- transform(preDf, MeanScore=mean(Score, na.rm=TRUE))) 

##    user  system elapsed 
##   0.001   0.000   0.002

1# plyr
2require(plyr)
3system.time(overallDf2 <- mutate(preDf, MeanScore=mean(Score, na.rm=TRUE)))

##    user  system elapsed 
##   0.002   0.000   0.002

1# dplyr
2require(dplyr)
3system.time(overallDf3 <- preDf %>% 
4                            mutate(MeanScore=mean(Score, na.rm=TRUE)))

##    user  system elapsed 
##   0.007   0.000   0.007

1# data.table
2require(data.table)
3preDt <- data.table(preDf)
4setkey(preDt, User)
5system.time(overallDt <- preDt[,list(User=User
6                                     ,Session=Session
7                                     ,Score=Score
8                                     ,MeanScore=mean(Score, na.rm=T))])

##    user  system elapsed 
##   0.007   0.000   0.007

1# dplyr + data.table
2system.time(overallDf4 <- preDt %>% 
3                            mutate(MeanScore=mean(Score, na.rm=TRUE))) 

##    user  system elapsed 
##   0.003   0.000   0.003

Adding average by user

It takes quite long using plyr and other packages would be more practial - base is not considered even.

1# plyr
2require(plyr)
3system.time(postDf1 <- ddply(preDf
4                             ,.(User)
5                             ,mutate,MeanScore=mean(Score, na.rm=TRUE))) 

##    user  system elapsed 
##  76.488   0.522  76.990

1# dplyr
2require(dplyr)
3system.time(postDf2 <- preDf %>% 
4              group_by(User) %>% 
5              mutate(MeanScore=mean(Score, na.rm=TRUE)) %>% 
6              arrange(User))

##    user  system elapsed 
##   0.022   0.006   0.028

1# data.table
2require(data.table)
3preDt <- data.table(preDf)
4setkey(preDt, User)
5system.time(postDt <- preDt[,list(Session=Session
6                                  ,Score=Score
7                                  ,MeanScore=mean(Score, na.rm=T))
8                            ,by=User])

##    user  system elapsed 
##   0.005   0.004   0.009

1# dplyr + data.table
2system.time(postDf3 <- preDt %>% 
3              group_by(User) %>% 
4              mutate(MeanScore=mean(Score, na.rm=TRUE)) %>% 
5              arrange(User))

##    user  system elapsed 
##   0.008   0.004   0.012