Python User Learning R

Just as I’m getting a feel for python, why not tack on another language. R is very popular for statistical computing, and the number of packages R has for this functionality confirms that intuition.

So in order to be maximally effective in my graduate work (and use the right model for the job), I should at least have a passing knowledge of R in addition to python. I am using this blog format to chronicle my adventures and missteps while learning R.

WYSIWYG (what you see is what you get)

This is the assumption I’ve operated under with python. When I make a list and print out the results, I get something like this:

list(1, 2, 3, 4, 5)
[1, 2, 3, 4, 5]

I explicitly see the structure of the list and the straight brackets tell me this is a list as opposed to parens which would indicate a tuple.

However in R, I may get something like:

c(1, 2, 3, 4, 5)
[1] 1 2 3 4 5

It took me a little while to get comfortable that the [1] prepended is a convenience to show which line the results are being printed out to. R gets more confusing when trying to show a more complex object. However, I’m beginning to appreciate R as an interactive programming language, and the seemingly strange way to print data structures is great for the interactive user who does not need to concern themselves with the underlying data structures R is using.

But if you are interested in the structure, then you should use the struct() function, which will bring it closer to what I’m used to seeing in python and help me understand the data types I use in R.

The next post will probably be about non-standard evaluation (this still blows my mind)