Remove rows with NAs (missing values) in data.frame
I'd like to remove the lines in this data frame that contain NA s 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
Also, I'd like to know how to only filter for some columns, so I can also get a data frame like this:
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
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.
Try na.omit(your.data.frame) . As for the second question, try posting it as another question (for clarity).
I prefer following way to check whether rows contain any NAs:
row.has.na <- apply(final, 1, function(x){any(is.na(x))})
This returns logical vector with values denoting whether there is any NA in a row. You can use it to see how many rows you'll have to drop:
sum(row.has.na)
and eventually drop them
final.filtered <- final[!row.has.na,]
For filtering rows with certain part of NAs it becomes a little trickier (for example, you can feed 'final[,5:6]' to 'apply'). Generally, Joris Meys' solution seems to be more elegant.
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