Comment by jme3 | Hacker News Reader

Comment by jme3 | Hacker News Reader

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This pretty much perfectly illustrates my comment below, pointing out that these sorts of recommendations are entirely subjective and useless.

Many of your points are quite subjective. I could do the same thing with Matlab. For instance, I find it mind boggling that anyone could get anything done when you have to devote a separate file to every single functions. That seems incomprehensible to me. And yet, I realize that that's probably a mostly subjective thing that you get used to.

Personally, I find R's documentation excellent. When people complain about it, it's usually because they have mistaken it for a tutorial. It's not. It's documentation.

Without any data, I seriously doubt your claim that Matlab has a much larger user base. (There is considerably more activity in R on StackOverflow than in Matlab.)

Your complaint about matrices, lists and data frames is similar. Data frames exist for the same reason that there's a mean() function: a columnar data structure that holds differently data types in each column comes up so often and is considered so useful that it is built in.

pandas in Python was developed in a way that went out of its way to specifically _mimic_ these data structures because data frames are considered such a vital aspect of R.

And keep in mind that these criticisms are all coming from someone who _also_ recommended against switching...!

You make good points, however I have to take issue with the documentation.

> When people complain about it, it's usually because they have mistaken it for a tutorial. It's not. It's documentation.

I don't really see the distinction. Documentation is supposed to explain to you how to use the code. You can call it whatever you want. If it's through a tutorial, then why not. R - and especially the non-standard packages you download through CRAN - have very terse documentation that barely explain how each function works on it's own, and much less how it works in the context of the rest of the package. You can't just tell the user what goes into the black box and what comes out and expect people to be able to use your software.

Sure they're are vignettes (I think that's the term), but they're really inadequate b/c they only scratch the surface of how the package is meant to be used.

Anyways, that's my 2 cents. I've spent soooo many hours fighting with R documentation trying to figure out how to get what I needed done. Sometimes months later I would find out there is a much better way to do something that simply was not explained anywhere. I'm OK at R now, but I went through a lot of pain to get to where I am now. I'd never wish it on anyone else.

My experience with MATLAB on the other hand has always been very pleasant. I spent like 3 hours going over the tutorial on how to use it (much better then R's "Introduction to R") and I hit the ground running. When I needed something a quick search through the help or online always turned up results.

From my memory, MATLAB's documentation not only discusses the implementation, but also discusses the statistical/engineering methodology. It's overkill and can be pretty annoying (paging back and forth between different parts of the help can be somewhat time consuming) when you actually know the statistics but just want to understand the implementation. Hence the distinction between "documentation" and "a tutorial".

I don't know whether it's an explicit or implicit design choice or just a happy accident, but I'm grateful that the R documentation doesn't try to hold anyone's hand and guide them through data analysis beyond their training.

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