The downside of this first approach is having too many functions, code repetition because of some variables that are in common between datasets. Meanwhile, the downside of the second approach is that the function will be too big, and harder to manage.
Initially, here's the idea. One function per data set
add_labels_households(arrw, lang = c('PT', 'EN'))add_labels_population(arrw, lang = c('PT', 'EN'))add_labels_mortality(arrw, lang = c('PT', 'EN'))Depending on how it goes, it might be better to have a single function that applies to different data sets. E.g.
add_labels(arrw, dataset = c('households', 'population', 'mortality'), lang = c('PT', 'EN'))The downside of this first approach is having too many functions, code repetition because of some variables that are in common between datasets. Meanwhile, the downside of the second approach is that the function will be too big, and harder to manage.