Calculate mean across rows with NA values in R

Question

I have a really simple R question but I can\'t seem to find an adequate solution. Let\'s say we have the following data frame:

groupid<-rep(1:5, each=3)
n         


        

Answer 1

testscores$testMean <- rowMeans(testscores[,3:4], na.rm=TRUE)
> testscores
   groupid    names test1 test2 testMean
1        1     Bill    90    80     85.0
2        1      Jim    70    NA     70.0
3        1    Sarah    90    92     91.0
4        2     Mike    NA    80     80.0
5        2 Jennifer   100    65     82.5
6        2     Bill    90    80     85.0
7        3      Jim    70    NA     70.0
8        3    Sarah    90    92     91.0
9        3     Mike    NA    80     80.0
10       4 Jennifer   100    65     82.5
11       4     Bill    90    80     85.0
12       4      Jim    70    NA     70.0
13       5    Sarah    90    92     91.0
14       5     Mike    NA    80     80.0
15       5 Jennifer   100    65     82.5

Answer 2

you can also use this

testscores <- structure(list(groupid = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 
4L, 4L, 4L, 5L, 5L, 5L), names = structure(c(1L, 3L, 5L, 4L, 
2L, 1L, 3L, 5L, 4L, 2L, 1L, 3L, 5L, 4L, 2L), .Label = c("Bill", 
"Jennifer", "Jim", "Mike", "Sarah"), class = "factor"), test1 = c(90, 
70, 90, NA, 100, 90, 70, 90, NA, 100, 90, 70, 90, NA, 100), test2 = c(80, 
NA, 92, 80, 65, 80, NA, 92, 80, 65, 80, NA, 92, 80, 65)), .Names = c("groupid", 
"names", "test1", "test2"), row.names = c(NA, -15L), class = "data.frame")

testscores$meanTest=rowMeans(testscores[,c("test1", "test2")], na.rm=TRUE)

#   groupid    names test1 test2 meanTest
#1        1     Bill    90    80     85.0
#2        1      Jim    70    NA     70.0
#3        1    Sarah    90    92     91.0
#4        2     Mike    NA    80     80.0
#5        2 Jennifer   100    65     82.5
#6        2     Bill    90    80     85.0
#7        3      Jim    70    NA     70.0
#8        3    Sarah    90    92     91.0
#9        3     Mike    NA    80     80.0
#10       4 Jennifer   100    65     82.5
#11       4     Bill    90    80     85.0
#12       4      Jim    70    NA     70.0
#13       5    Sarah    90    92     91.0
#14       5     Mike    NA    80     80.0
#15       5 Jennifer   100    65     82.5