I would like to get the average for certain columns for each row.
I have this data:
w=c(5,6,7,8)
x=c(1,2,3,4)
y=c(1,2,3)
length(y)=4
z=data.frame(w,x,y)
Which returns:
w x y
1 5 1 1
2 6 2 2
3 7 3 3
4 8 4 NA
I would like to get the mean for certain columns, not all of them. My problem is that there are a lot of NAs in my data. So if I wanted the mean of x and y, this is what I would like to get back:
w x y mean
1 5 1 1 1
2 6 2 2 2
3 7 3 3 3
4 8 4 NA 4
I guess I could do something like z$mean=(z$x+z$y)/2 but the last row for y is NA so obviously I do not want the NA to be calculated and I should not be dividing by two. I tried cumsum but that returns NAs when there is a single NA in that row. I guess I am looking for something that will add the selected columns, ignore the NAs, get the number of selected columns that do not have NAs and divide by that number. I tried ??mean and ??average and am completely stumped.
ETA: Is there also a way I can add a weight to a specific column?