wildanimal

But if you look at Emacs-as-IDE route taken by EDE/CEDET suite, it's a kludgy beast... (I don't know how large the EDE/CEDET user community is, but most people I know forsake it in favor of the simpler facilities in Emacs).

I thought the plan was to rebase in Guile Scheme?

Can you get it through a host like sourceforge/github, or through a package manager like macports/homebrew? I can only find a zipped file on the web...

The original statement could be interpreted in this way: the former operation 'returns a function' and in the latter, it 'bind[s] [...] arguments' - suggesting a form of destructive updating of the original function. But I agree with you that in this context, since both return functions it's an implementation detail.

I wouldn't discourage them uniquivocally - for instance, 'subset' is an idiom often used in the context of data/relational tables. That matters a little bit (enough to pay a little penalty in raw performance), I would think.

I couldn't tell from the first chapter, but are there a lot of equations? If so, would be a big plus for me.

How is this better than attaching data to objects and operating on them with its methods? (Seriously, I would like to know). The syntax does not look all that different and with classes you can additionally have inheritance by which you can "get" a lot of relevant methods for free...

That sounds great -- I only recently learned of pandas (I normally don't use much of NumPy/SciPy), but I will keep an eye out on this.

I entirely agree though my personal preference is for lattice over ggplot as it is faster and more flexible at the present time (the "limitations" of ggplot reflect the preference of the creator; e.g. not being able to have two axes for the same plot). But reshape and also plyr are quite useful.

R does have surprising capability for shell scripting and text processing, albeit slower than Python. I also use Python for the rapid text-processing necessary (possibly populating an SQL database) for R to eventually use.

I've been keeping an eye on SciPy, but there still seems to be a lot of "the source code is the documentation", whereas in R the documentation is usually superb and well-structured. And Matplotlib, while beautiful, seems to be more verbose than Matlab or R when it comes to customizing details of the graphics (e.g., axes, etc.). That's just my impression, but I wouldn't mind being shown otherwise.

can use virtualbox+windows. not ideal, but one way.

Agreed -- the author of the post is talking about writing or debugging algorithms; coding is the stuff you need your computer for.