Dear R users,
I??ve got a simple question but somehow I can??t find the solution:
I have a data frame with columns 1-5 containing one set of integer values,
and columns 6-10 containing another set of integer values. Columns 6-10
contain NA??s at some places.
I now want to calculate
(1) the number of values in each row of columns 6-10 that were NA??s
(2) the sum of all values on columns 1-5 for which there were no missing
values in the corresponding cells of columns 6-10.
Example: (let??s call the data frame "data")
Col1 Col2 Col3 Col4 Col5 Col6 Col7 Col8 Col9 Col10
1 2 5 2 3 NA 5 NA 1 4
3 1 4 5 2 6 NA 4 NA 1
The result would then be (for the first row)
(1) "There were 2 NA??s in columns 6-10."
(2) The mean of Columns 1-5 was 2+2+3=7" (because there were NA??s in the
1st and 3rd position in rows 6-10)
So far, I know how to calculate the rowSums for the data.frame, but I
don??t know how to condition these on the values of columns 6-10
rowSums(data[,1:5]) #that??s straightforward
apply(data[,6:19],1,function(x)sum(is.na(x))) #this also works fine
But I don??t know how to select just the desired values of columns 1-5 (as
described above)