Today I saw a link question from reddit: How important is Java/C++ vs just using R/Matlab for big data? I learned C++ and Matlab when I was undergraduate and I am now using R by self learning as a PhD student in Stats Department. But living in this big data time, R is really not enough for scientific computing. Hence this link question is really what I want to know. Here I want to organize the interesting materials, including posts, about the programming, especially R and C++.
- Ruby and Ruby on Rails
Ruby is a dynamic, object-oriented, open-source programming language; Ruby on Rails is an open-source Web application framework written in Ruby that closely follows the MVC (Model-View-Controller) architecture. With a focus on simplicity, productivity and letting the computers do the work, in a few years, its usage has spread quickly. Ruby is very similar to Python, but with different syntax and libraries. There’s little reason to learn both, so unless you have a specific reason to choose Ruby (i.e. if this is the language your colleagues all use), I’d go with Python.
Python is an interpreted, dynamically-typed programming language. Python programs stress code readability, so even non-programmers should be able to decipher a Python program with relative ease. This also makes the language one of the easiest to learn and write code in quickly. Python is very popular and has a strong set of libraries for everything from numerical and symbolic computing to data visualization and graphical user interfaces.
Java is an object-oriented programming language developed by James Gosling and colleagues at Sun Microsystems in the early 1990s. Why you should learn it: Hailed by many developers as a “beautiful” language, it is central to the non-.Net programming experience. Learning Java is critical if you are non-Microsoft.
What is PHP? PHP is an open-source, server side html scripting language well suited for web developers as it can easily be embedded into standard html pages. You can run 100% dynamic pages or hybrid pages, 50% html + 50% php.
C is a standardized, general-purpose programming language. It’s one of the most pervasive languages and the basis for several others (such as C++). It’s important to learn C. Once you do, making the jump to Java or C# is fairly easy, because a lot of the syntax is common. C is a low-level, statically typed, compiled language. The main benefit of C is its speed, so it’s useful for tasks that are very computationally intensive. Because it’s compiled into an executable, it’s also easier to distribute C programs than programs written in interpreted languages like Python. The trade-off of increased speed is decreased programmer efficiency. C++ is C with some additional object-oriented features built in. It can be slower than C, but the two are pretty comparable, so it’s up to you whether these additional features are worth it.
Perl is an open-source, cross-platform, server-side interpretive programming language used extensively to process text through CGI programs. Perls power in processing of piles of text has made it very popular and widely used to write Web server programs for a range of tasks.
This rank is only for the users on GitHub, which is biased for you. For me, I think C/C++, R, Julia, Matlab, Java, Python, Perl will be popular among stats sphere.
- Advice on learning C++ from an R background
- Integrating C or C++ into R, where to start?
- R for testing, C++ for implementation?
- Some thoughts on Java—compared with C++
- A list of RSS C++ blogs
- Get started with C++ AMP
- C++11 Concurrency Series
- Google’s Python Class and Google’s C++ Class from Google Code University
- Integrating R and C++
- Learn Python on Codecademy
- Learn How to Code Without Leaving Your Browser
- Minimal Advice to Undergrads on Programming
- Learning R Via Python (or the other way around).
- Bloom teaches Python for Scientific Computing at Berkeley (available as a podcast).
What are the three most important programming languages to learn?—The following is from Waleed Kadous, PhD in Computer Science:I would focus on learning three classes of languages to really understand the nature of programming and to have a decent toolkit. Everything else is basically variants on that.Learn a low-level language so you understand what goes on at the bare metal and so you can make hardware dance
The obvious choice here is C, but assembly language might also be good.Learn a language for architecting large systems
If you want to build large code bases, you’re going to need one of the strongly typed languages. Personally, I think Java is the best choice here; but C++, Scala and even Ada are acceptable.Learn a language for scripting things together quickly
There are a few choices here: shell, Python, Perl, Lua. Any of these will do, but Python is probably the foremost. These are great for gluing existing pieces together.
Now, if you only get three, that’s it. But I’m going to suggest two more categories.
Learn a language that forces you to think differently about programming
These are majorly different world perspectives. Examples here would be functional programming, like Haskell, ML, etc, but also logic programming like Prolog.
Learn a language that lets you build web-based applications quickly