Let me reclaim my question, how I can sum the numbers by row, and list the sum follow by the last column, forming a new column like the second table (sum = a + b+ c + d + e)?
And I also want to know what if some of the values are N/A, can I still treat them as numbers?
Sample input:
a b c d e
1 90 67 18 39 74
2 100 103 20 45 50
3 80 87 23 44 89
4 95 57 48 79 90
5 74 81 61 95 131
Desired output:
a b c d e sum
1 90 67 18 39 74 288
2 100 103 20 45 50 318
3 80 87 23 44 89 323
4 95 57 48 79 90 369
5 74 81 61 95 131 442
To add a row sum, you can use addmargins
M <- matrix(c(90,67,18,39,74), nrow=1)
addmargins(M, 2) #2 = row margin
# [,1] [,2] [,3] [,4] [,5] [,6]
# [1,] 90 67 18 39 74 288
If you have missing data, you'll need to change the margin function to something that will properly handle the NA values
M<-matrix(c(90,67,18,NA,74), nrow=1)
addmargins(M, 2, FUN=function(...) sum(..., na.rm=T))
# [,1] [,2] [,3] [,4] [,5] [,6]
# [1,] 90 67 18 NA 74 249
Consider using apply(). For example:
set.seed(10) # optional, but this command will replicate data as shown
# create some data
x <-matrix(rnorm(1:25),nrow=5,ncol=5) # 5x5 matrix of random numbers
x
[,1] [,2] [,3] [,4] [,5]
[1,] 0.01874617 0.3897943 1.1017795 0.08934727 -0.5963106
[2,] -0.18425254 -1.2080762 0.7557815 -0.95494386 -2.1852868
[3,] -1.37133055 -0.3636760 -0.2382336 -0.19515038 -0.6748659
[4,] -0.59916772 -1.6266727 0.9874447 0.92552126 -2.1190612
[5,] 0.29454513 -0.2564784 0.7413901 0.48297852 -1.2651980
x.sum <-apply(x,1,sum) # sum the rows. Note: apply(x,2,sum) sums cols
x.sum
[1] 1.003356605 -3.776777904 -2.843256446 -2.431935624 -0.002762636
# attach new column (x.sum) to matrix x
x.sum.1 <-cbind(x,x.sum)
x.sum.1
x.sum
[1,] 0.01874617 0.3897943 1.1017795 0.08934727 -0.5963106 1.003356605
[2,] -0.18425254 -1.2080762 0.7557815 -0.95494386 -2.1852868 -3.776777904
[3,] -1.37133055 -0.3636760 -0.2382336 -0.19515038 -0.6748659 -2.843256446
[4,] -0.59916772 -1.6266727 0.9874447 0.92552126 -2.1190612 -2.431935624
[5,] 0.29454513 -0.2564784 0.7413901 0.48297852 -1.2651980 -0.002762636
Let's say you have the dataframe df, then you could try something like this:
# Assuming the columns a,b,c,d,e are at indices 1:5
df$sum = rowSums(df[ , c(1:5)], na.rm = T)
Or you could aslo try this:
transform(df, sum=rowSums(df), na.rm = T)
