This can also demonstrate how they can be used with the new shiny vis_expect function from visdat.

drop_na_at currently drops NAs and returns only columns for which missing values have been dropped. This might be less useful if one would like to do the analysis at once.

The package does not focus on imputation(just exploration) so it would be great to keep the entire dataset intact. Stated differently, one should drop_na_at if such a drop results in equal number of rows(highly unlikel