Question

I have a CSV of file of data that I can load in R using read.csv()

Some of the data is missing, so I want to reduce the data frame down to set that consists entirely of non-missing data, i.e. if a NULL appears anywhere, I want to exclude that column and row from the filtered data set.

I know I can probably do this fairly simply with the inbuilt R vector operations, but I am not quite sure how to do this exactly?

To make my question a little more concrete, here is a quick sample of the data so you can see what I want to do.

DocID       Anno1    Anno7  Anno8 1           7        NULL   8 2           8        NULL   3 44          10       2      3 45          6        6      6 46          1        3      4 49          3        8      5 62          4        NULL   9 63          2        NULL   4 67          11       NULL   3 91          NULL     9      7 92          NULL     7      5 93          NULL     8      8 

So given this input, I need some code that will reduce the output to this.

DocID       Anno8 44          3 45          6 46          4 49          5 

As Anno8 is the only column with non-NULL data, and there are only four rows with non-NULL data.

Answer 1

If x is your data.frame (or matrix) then

x[ ,apply(x, 2, function(z) !any(is.na(z)))] 

Since your example uses NULL, is.na(·) will be replaced by is.null(·)

Alternatively you can look at subset(·).