Count number of non-NA values for every column in a dataframe

Question

I have a big dataset that contains a lot of NAs and some non-Na values. At the moment I count my non-NA values for each column like this:

Answer 1

With dplyr, that would be:

library(dplyr)

df %>%
summarise_all(funs(sum(!is.na(.)))

The advantage of that approach is that you can use group_by before, and that you don't need to care about column names (it just summarizes all of them).