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.

Answer 1

We can also use the subset function for this.

finalData<-subset(data,!(is.na(data["mmul"]) | is.na(data["rnor"])))

This will give only those rows that do not have NA in both mmul and rnor

Answer 2

tidyr has a new function drop_na:

library(tidyr)
df %>% drop_na()
#              gene hsap mmul mmus rnor cfam
# 2 ENSG00000199674    0    2    2    2    2
# 6 ENSG00000221312    0    1    2    3    2
df %>% drop_na(rnor, cfam)
#              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 3

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

Answer 4

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.

Answer 5

Using dplyr package we can filter NA as follows:

dplyr::filter(df,  !is.na(columnname))

Answer 6

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.