[R] "apply" question

[Liaw, Andy]

Try:

> ## Number of NAs in columns 6-10.
> colSums(is.na(data[6:10]))
 Col6  Col7  Col8  Col9 Col10 
    1     1     1     1     0 
> 
> ## Number of NAs in each row of columns 6-10.
> rowSums(is.na(data[6:10]))
1 2 
2 2 
> 
> ## Sums of rows 1-5 omitting corresponding NAs in cols 6-10.
> rowSums(data[,1:5] * !is.na(data[,6:10]))
1 2 
7 9 

If all entries are numeric, it'd be easier to use matrices instead of data
frames.

HTH,
Andy

> From: Christoph Scherber
> 
> 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)
> 
> 
> Can anyone help me? Thanks a lot in advance!
> 
> Best regards
> Christoph
> 
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