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Comment by AuthorizedCust | Hacker News Reader

R plus the tidyverse is what makes it a great language. Some tidyverse concepts are being baked into base R, like the pipe, but base R by itself feels hollow.

R’s future is inseparable from the tidyverse. We need to just lump them together in any serious discussion of R.

I teach a graduate level R course mainly for economics and statistics majors. (My educational background and career are computer science and technical; while that may stereotype me into Python, I just love R.) I spend the first three weeks on base R, to convey language-essential concepts, like vectorized objects, then the rest of the course is tidyverse-centric.

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Just for the record, many users are happy with base R. There are dozens of us!

R by itself is nice. But the tidyverse is creeping in and bringing dependency hell with it.

http://www.tinyverse.org/

hard second. ggplot2 was the last (only) good package hadley ever wrote; the rest is more about reinventing the wheel and viral-marketing with hex-stickers than about getting work done. the newer stuff in particular is atrocious; heaven forfend function calls that don't require understanding the lore of a package (`recipes` has stupid functions like `recipe`, `bake` and similar nonsense).

at a push, base + data.table + ggplot2 get everything done. tinyverse ftw.

For those that don’t know the “tidyverse” is a set of R packages that make using base R much easier/better (in my opinion)

https://www.tidyverse.org/ There is also a free ebook that’s a good reference.

ggplot2 the plotting package included is pretty awesome

I took a biostatistics class and after the basic examples in R using the tidyverse to analyze data for projects was very helpful.

Personally I much prefer data.table. The syntax is a bit harder to get a handle on, but you can do just about anything with it, and it's much faster at runtime than tidyverse.

  I spend the first three weeks on base R, to convey language-essential concepts ...

Awesome. When I was at Berkeley, Linear Systems had Matlab assignments. The real engineers (ME, CE, NE, ...) had taken a Matlab class and knew the language. We computer scientists hadn't and suffered horribly as a consequence. Your three weeks of learning base R instead of sink or swim will pay dividends.

Got the reverse experience. Trained in Matlab, R and Python, we had to follow a database/application class with computer scientist and software engineers where the big project was to make a basic Android application with sqlite database. That was painfully to be dropped in Android Studio without any Java knowledge. And because the class was focused on database, we had no Java introduction or whatever. We were able to team up with students from the other cursus that already had multiple Java projects and classes under their belt but the pill was bitter swallow.

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