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Why aren't these various encodings allowing me to properly display Portuguese?
(2 answers)
Closed 1 year ago.
When I first wrote my script, letters such as 'ç' and 'ã - very commonly used in portuguese - were fine. So if I wrote, for example, the word 'vagão' in portuguese, that's how it would read it. But when I reopened the project with that script, it reads "vagão". How do I fix it?
You must be looking at encoding issues or conversion issues due to encoding on Windows(assuming that you're using windows). This might give you your answer.
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How is Racket different from Scheme?
(6 answers)
Closed 9 years ago.
Is there a big difference betwen the languages Racket and Scheme? In the book How to Design Programs (HtDP2e) they teach you Racket, but in the famous SICP it is Scheme. I am going to read these books simultaneously, what should I be aware of?
SICP uses R4RS Scheme while HtDP uses a stripped down lexical Scheme-like language. Lang #racket is originally a R5RS with a propretary module system, but it has adopted some R6RS features as well as going their own way with their immutable pairs.
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Closed 11 years ago.
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How to develop a package in R?
I read some material about making R package and get confuse.
Could any one illustrate simple and easy steps of making R package on windows for both operating system(windows and linux) with C++ code file?
Thanks
I suggest you to have a look at Hadley Wickham recomendations:
Hadley Wiki
Hadley Package basics
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Is there any standard logging package for R? [closed]
(7 answers)
Closed 8 years ago.
Which logging package would you recommend for R? I am aware there are several packages available but would like to know which one is considered the best. Specifically, here is what I am looking for:
multiple logging level
built-in support for rotating log file
fast (should not slow down too much existing code)
painless to setup (not too much boilerplate code)
For simple logging, evaluate ?sink
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I'd like to know how to learn the R language as as 'programming' language as opposed to learning it as a statistical system. My question is prompted by lack of understanding of such functions as parse, eval, etc. which may not find frequent use by an R user with a 'statistics' persuasion.
Edit: I've been exploring such tools like Rpy RSPerl rJava and wish to (at the very least) be able to understand concepts that facilitate R's communication with other programming languages.
The availability of Web applications for R (R-PHP, RApache, etc.) is another motivationg factor for me to gain a deeper, more structural understanding of R.
Last but not the least, I'd like to be able to write R packages for which such understanding would be beneficial if not necessary.
For starters, you might want to look at this article by John Cook. Also make sure that you read "The R Inferno".
There are many good resources on the R homepage, but in particular, read "An Introduction to R" and "The R Language Definition".
Some very closely related stackoverflow questions:
books-for-learning-the-r-language.
what-are-some-good-books-web-resources-and-projects-for-learning-r
suggestions-on-way-resources-to-start-learning-statistical-language-r
My favorite book on the subject: "Software for Data Analysis: Programming with R", by John Chambers, the creator of the S language.
(source: springer.com)
A good book for learning R-as-a-programming-language (as opposed to R-for-statistics) is The Art of R Programming, by Norman Matloff.
It's very readable, doesn't assume you're a computer scientist, and is quite inexpensive as R books go.
I would rather suggest a good and comprehensive start, like The R Book by Michael Crawley. It's an easy-to-read and complete book on R core functions, with statistical tips and a few exercises. It focuses a lot on R strengths (e.g. linear models) and gives also useful coding tricks. It helped me a lot while I was struggling on cryptic online courses.
I'm a very hands-on learner, so this advice may be specific to my learning style. I would suggest that the best place to start "learning to program" in any language involves finding problems outside of your normal range of experience and then trying to solve them using a programming language.
The projects that taught me the most about how to program with R had nothing to do with statistics at all.
Knowing functions like parse() and eval() is by no means a measure for being "a good R programmer". Applications that require heavy use of these functions do not make up a majority of the problem space in which you can apply R. Instead, I think you should try to be "a good programmer" who knows R. This involves refining your problem-solving approaches.
Programming is not a spectator sport-- a good book is indispensable as a reference on the tools available, but you need to find some problems upon which to hone your skills.