----- Original Message ----- From: "Christoph Scherber" <[EMAIL PROTECTED]>
To: <r-help@stat.math.ethz.ch>
Sent: Monday, May 02, 2005 10:52 AM
Subject: [R] "apply" question
Dear R users,
Iīve got a simple question but somehow I canīt 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 NAīs at some places.
I now want to calculate
(1) the number of values in each row of columns 6-10 that were NAīs
(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: (letīs 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 NAīs in columns 6-10."
(2) The mean of Columns 1-5 was 2+2+3=7" (because there were NAīs 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 donīt know how to condition these on the values of columns 6-10
rowSums(data[,1:5]) #thatīs straightforward apply(data[,6:19],1,function(x)sum(is.na(x))) #this also works fine
But I donīt know how to select just the desired values of columns 1-5 (as described above)
tmp <- rowSums(data[apply(data[,6:19],1,function(x) sum(is.na(x)))==0,1:5])
Now, tmp contains only the rowsums for the rows with no NAs in the other columns.
Sean
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