[R] score counts in an aggregate function

[KDT]

Dear R-Users,
I have a big data set "mydata" with repeated observation and some missing
values. It looks like the format below:

userid sex item score1  score2
1         0    1      1         1
1         0    2      0         1
1         0    3      NA       1 
1         0    4      1         0
2         1    1      0         1
2         1    2      NA       1
2         1    3      1         NA
2         1    4      NA       0
3         0    1      1         0
3         0    2      1         NA
3         0    3      1         0
3         0    4      0         0

I wound like to summarise the dataset such that i get something in the
format of 

userid sumscore1  countscore1  meanscore1 sumscore2  countscore2  
meanscore2  
1          2                    3            0.67              3              
4              0.75
2          1                    2            0.5                2             
3               0.67
3          3                    4            0.75              0              
3               0.00

I tried using :
means <- data.frame(aggregate(mydata[,
4:5],by=list(mydata$userid),FUN="mean", na.rm="TRUE"))
and
sums <- data.frame(aggregate(mydata[, 4:5],by=list(mydata$userid),FUN="sum",
na.rm="TRUE"))

so that i could merge the two data.frames later. This works quite okay but i
still can not get a function that can give me a data.frame for the counts!!
Something like this::
counts <- data.frame(aggregate(mydata[,
4:5],by=list(mydata$userid),FUN="count", na.rm="TRUE")).

Any advice?

Trevor
Belgium

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