I’m frequently asked by newcomers to R to provide an easy to follow generic set of instructions on how to download data, transform it, aggregate it, make graphs, and write it all up for publication in a high impact journal – all by the end of the day ! While such a request is somewhat understandable coming from a student it’s somewhat awkward when coming from a seasoned research investigator, (i.e. someone who should know better). Obviously, no such set of instructions exists given the astonishing variety of available data stored in differing formats with varying degrees of adherence to a standard(s). Simply put, “real world” data wrangling and analysis can be a complex process independent of the language you choose to employ. Nonetheless, what I’ll attempt to do here is provide a “tour” involving some data I picked at random. I’ll be sticking to the problems of downloading, filtering…
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