A newcomer’s (angry) guide to R
I use R a lot and I have to say some of these comments are weird.<p>1. R and Lisp are hardly alike even if it was inspire by it. It&#x27;s like saying Erlang and Prolog is very similar. If you want learn FP do it in Erlang, Lisp, Haskell, etc.. Don&#x27;t do it in R, it&#x27;s half baked.<p>2. R syntax is ugly with warts. But built in datatype like dataframe, factor type, NA (missing value notion) value, make this language much better than many languages out there for dealing with data. Subsetting dataframe is a breeze even in base R.<p>3. There are many many advance statistical packages only in R. GLMnet was was in R for 4-5 years before someone decided to port it to Python. You can argue that there might be alternative package. But the statistician that created ridge, elastic, etc... method made GLMnet. There are many statistician out there that just implement their latest method in R. If you want to learn a subject in statistic there is probably a book out there and it&#x27;ll have an R package and code to come along with it. Next to that will be SAS. There are very few stat book with python packages. You want to learn bayesian statistic? Social Network Analysis? There&#x27;s a book for it with R code and a package to do that. Good luck finding one in Python for these subfield of statistic. There&#x27;s a bayesian hierarchical analysis in Ecology and that book is in R.<p>4. ggplot2 is amazing for static graphic. R doesn&#x27;t have good dynamic graphic out there and I kinda meh with Shiney. If you hate the syntax then you may learn to appreciate it by reading it from the creator <a href="https:&#x2F;&#x2F;www.r-bloggers.com&#x2F;a-simple-introduction-to-the-graphing-philosophy-of-ggplot2&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.r-bloggers.com&#x2F;a-simple-introduction-to-the-grap...</a>