One of the great things about R is that there's so much available to use with it: there are several interfaces to choose from, thousands of add-on packages to extend its capabilites, hundreds of books and on-line tutorials — an abundance of riches to improve your R experience. But with that abundance comes a problem: how to find the best add-ons to R.
Qin Wenfeng has taken the trouble to curate the best add-ons to R in their list, awesome-R: A curated list of awesome R frameworks, packages and software. The list provides several (but not too many!) recommendations for R users in the areas of IDEs, data manipulation packages, database integration frameworks, machine learning suites, R-related websites, and much more.
While your favourite add-on might not be listed in any given category (I would have added "checkpoint" to Reproducible Research, for example), on the whole the items listed merit their inclusion. If you find yourself overwhelmed with choices for R, this is a good place to start. And if you can't find what you're looking for, there's still the Task Views.
GitHub (Qin Wenfeng): Awesome R (via Alex Bresler)
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