Row based summary calculations

r

Solution

You can use `[` to select the relevant variables as in:

set.seed(007)
X <- data.frame(matrix(sample(c(10:20, NA), 100, replace=TRUE), ncol=10))
sex <- sample(c('F', 'M'), 10, T)
reg <- sample(c('N', 'S', 'E', 'W'), 10, T)
DF <- cbind(sex, reg, X)
DF # this is your data.frame
       sex reg X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
1    F   E NA 12 17 18 19 16 12 13 20  14
2    F   S 14 12 13 13 14 18 16 17 20  10
3    F   N 11 19 NA 12 19 19 19 20 12  20
4    F   E 10 11 20 12 15 17 18 17 18  12
5    M   E 12 15 NA 14 20 18 16 11 14  18
6    F   E 19 11 10 20 13 14 17 16 10  16
7    M   E 14 16 17 15 10 11 15 15 11  16
8    F   W NA 10 15 19 19 12 15 15 19  14
9    M   N 11 NA NA 20 20 14 14 17 14  19
10   F   W 15 13 14 15 NA 13 15 NA 15  12

As you can see the first to varibles are non-numeric. use `sapply(DF, class)` to see that.

Now using `[` as mentioned above you can choose all the numeric variables

DF[,-c(1,2)] # selecting all variables but 1 and 2

You can now perform your calculations on these varibles

transform(DF, SD=apply(DF[,-c(1,2)],1, sd, na.rm = TRUE))  # and so on
   sex reg X1 X2 X3 X4 X5 X6 X7 X8 X9 X10       SD
1    F   E NA 12 17 18 19 16 12 13 20  14 3.041381
2    F   S 14 12 13 13 14 18 16 17 20  10 3.020302
3    F   N 11 19 NA 12 19 19 19 20 12  20 3.865805
4    F   E 10 11 20 12 15 17 18 17 18  12 3.496029
5    M   E 12 15 NA 14 20 18 16 11 14  18 2.958040
6    F   E 19 11 10 20 13 14 17 16 10  16 3.596294
7    M   E 14 16 17 15 10 11 15 15 11  16 2.449490
8    F   W NA 10 15 19 19 12 15 15 19  14 3.201562
9    M   N 11 NA NA 20 20 14 14 17 14  19 3.356763
10   F   W 15 13 14 15 NA 13 15 NA 15  12 1.195229

Another alternative would be:

newDF <- DF[,sapply(DF, is.numeric)]
transform(DF, SD=apply(newDF,1, sd, na.rm = TRUE))
   sex reg X1 X2 X3 X4 X5 X6 X7 X8 X9 X10       SD
1    F   E NA 12 17 18 19 16 12 13 20  14 3.041381
2    F   S 14 12 13 13 14 18 16 17 20  10 3.020302
3    F   N 11 19 NA 12 19 19 19 20 12  20 3.865805
4    F   E 10 11 20 12 15 17 18 17 18  12 3.496029
5    M   E 12 15 NA 14 20 18 16 11 14  18 2.958040
6    F   E 19 11 10 20 13 14 17 16 10  16 3.596294
7    M   E 14 16 17 15 10 11 15 15 11  16 2.449490
8    F   W NA 10 15 19 19 12 15 15 19  14 3.201562
9    M   N 11 NA NA 20 20 14 14 17 14  19 3.356763
10   F   W 15 13 14 15 NA 13 15 NA 15  12 1.195229

I prefer this last one since you don't have to know which varible is numeric, R will select them for you.

Edit

This would be a better approach

Define a function for basic stats

  Stats <- function(x){
      Mean <- mean(x, na.rm=TRUE)
      SD <- sd(x, na.rm=TRUE)
      Min <- min(x, na.rm=TRUE)
      Max <- max(x, na.rm=TRUE)
      return(c(Mean=Mean, SD=SD, Min=Min, Max=Max))
    }

    cbind(DF, t(apply(newDF,1, Stats))) # Where newDF is define as above 
   sex reg X1 X2 X3 X4 X5 X6 X7 X8 X9 X10     Mean       SD Min Max
1    F   E NA 12 17 18 19 16 12 13 20  14 15.66667 3.041381  12  20
2    F   S 14 12 13 13 14 18 16 17 20  10 14.70000 3.020302  10  20
3    F   N 11 19 NA 12 19 19 19 20 12  20 16.77778 3.865805  11  20
4    F   E 10 11 20 12 15 17 18 17 18  12 15.00000 3.496029  10  20
5    M   E 12 15 NA 14 20 18 16 11 14  18 15.33333 2.958040  11  20
6    F   E 19 11 10 20 13 14 17 16 10  16 14.60000 3.596294  10  20
7    M   E 14 16 17 15 10 11 15 15 11  16 14.00000 2.449490  10  17
8    F   W NA 10 15 19 19 12 15 15 19  14 15.33333 3.201562  10  19
9    M   N 11 NA NA 20 20 14 14 17 14  19 16.12500 3.356763  11  20
10   F   W 15 13 14 15 NA 13 15 NA 15  12 14.00000 1.195229  12  15

Problem

Original source