Remove rows where all variables are NA using dplyr

I would suggest to use the wonderful janitor package here. Janitor is very user-friendly:

janitor::remove_empty(dat, which = "rows")

Since dplyr 0.7.0 new, scoped filtering verbs exists. Using filter_any you can easily filter rows with at least one non-missing column:

# dplyr 0.7.0
dat %>% filter_all(any_vars(!is.na(.)))

Using @hejseb benchmarking algorithm it appears that this solution is as efficient as f4.

UPDATE:

Since dplyr 1.0.0 the above scoped verbs are superseded. Instead the across function family was introduced, which allows to perform a function on multiple (or all) columns. Filtering rows with at least one column being not NA looks now like this:

# dplyr 1.0.0
dat %>% filter(if_any(everything(), ~ !is.na(.)))