I like learning languages and after a little kerfuffle with a Python package I was wondering if there was anything out there for statistical data analysis that might not have so many hidden pitfalls in ordinary places.
I knew about R from colleagues but I never payed much attention to it, but I decided to give it a whirl. Here are some brief preliminary notes in no particular order
PLUS
MINUS
PLUS
- Keyword arguments!
- Gorgeous plotting
- Integrated workspace (including GUI package manager)
- Very good documentation and help
- NaN different from NA
- They have their own Journal. But what do you expect from a bunch of mathematicians?
- Prints large arrays on multiple lines with index number of first element on each line on left gutter
- Parenthesis autocomplete on command line
- RStudio, though the base distribution is pretty complete, with package manager, editor and console.
MINUS
- Everything is a function. I love this, but it means commands in the interpreter always need parentheses. I'd gotten used to the Python REPL not requiring parentheses.
- The assignment operator is two characters rather than one
- Indexing starts from 1. Oh god, could we PLEASE standardize this either way?
- Not clear how well R handles "big data" (Data that can't be loaded into memory at once) or parallelization. (To look up: bigmemory)
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