Remove rows with all or some NAs (missing values) in data.frame

Question

I'd like to remove the lines in this data frame that:

a) contain NAs across all columns. Below is my example data frame.

             gene hsap mmul mmus rnor cfam 1 ENSG00000208234    0   NA   NA   NA   NA 2 ENSG00000199674    0   2    2    2    2 3 ENSG00000221622    0   NA   NA   NA   NA 4 ENSG00000207604    0   NA   NA   1    2 5 ENSG00000207431    0   NA   NA   NA   NA 6 ENSG00000221312    0   1    2    3    2 

Basically, I'd like to get a data frame such as the following.

             gene hsap mmul mmus rnor cfam 2 ENSG00000199674    0   2    2    2    2 6 ENSG00000221312    0   1    2    3    2 

b) contain NAs in only some columns, so I can also get this result:

             gene hsap mmul mmus rnor cfam 2 ENSG00000199674    0   2    2    2    2 4 ENSG00000207604    0   NA   NA   1    2 6 ENSG00000221312    0   1    2    3    2 

Answer 1

Also check complete.cases :

> final[complete.cases(final), ]              gene hsap mmul mmus rnor cfam 2 ENSG00000199674    0    2    2    2    2 6 ENSG00000221312    0    1    2    3    2 

na.omit is nicer for just removing all NA's. complete.cases allows partial selection by including only certain columns of the dataframe:

> final[complete.cases(final[ , 5:6]),]              gene hsap mmul mmus rnor cfam 2 ENSG00000199674    0    2    2    2    2 4 ENSG00000207604    0   NA   NA    1    2 6 ENSG00000221312    0    1    2    3    2 

Your solution can't work. If you insist on using is.na, then you have to do something like:

> final[rowSums(is.na(final[ , 5:6])) == 0, ]              gene hsap mmul mmus rnor cfam 2 ENSG00000199674    0    2    2    2    2 4 ENSG00000207604    0   NA   NA    1    2 6 ENSG00000221312    0    1    2    3    2 

but using complete.cases is quite a lot more clear, and faster.

Answer 2

Try na.omit(your.data.frame). As for the second question, try posting it as another question (for clarity).