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Johnny-Five R Programming Welcome to the R programming Wikibook This book is designed to be a practical guide to the R programming language[1]. R is free software designed for statistical computing. There is already great documentation for the standard R packages on the Comprehensive R Archive Network (CRAN)[2] and many resources in specialized books, forums such as Stackoverflow[3] and personal blogs[4], but all of these resources are scattered and therefore difficult to find and to compare. The aim of this Wikibook is to be the place where anyone can share his or her knowledge and tricks on R. It is supposed to be organized by task but not by discipline[5]. How can you share your R experience ? Explain the syntax of a commandCompare the different ways of performing each task using R.Try to make unique examples based on fake data (ie simulated data sets).As with any Wikibook please feel free to make corrections, expand explanations, and make additions where necessary. Some rules : Prerequisites[edit] See also[edit]

R-bloggers | R news & tutorials from the web HTTP+JSON Services in Modern Java At Airbnb, we build most of our user facing apps in Ruby on Rails, or more recently Node.js and our own Rendr framework. We also have a number of internal services, and those are mainly written in Java for stability and performance. Coming from a Ruby world, building anything in Java can feel pretty painful and boring. But thankfully there are modern Java libraries that make it easy and even fun. We build our Java services with Twitter Commons, a collection of libraries for building HTTP (and other) services. The Stack Twitter Commons uses Jetty, and provides a lot of the glue and miscellaneous parts of a web service, like logging, statistics, registration, and lifecycle management. On top of Jetty we use Jersey and Jackson, which is a tried and true combination that is also used by other stacks like Yammer’s Dropwizard. Jetty is an incredibly fast embeddable web server and servlet container. Jackson is the de facto standard for fast JSON processing on the JVM. Example App Using the Service

R Starter Kit R Starter Kit This page is intended for people who: These materials have been collected from various places on our website and have been ordered so that you can, in step-by-step fashion, develop the skills needed to conduct common analyses in R. Getting familiar with R Class notes: There is no point in waiting to take an introductory class on how to use R. Recommended Books Introducing R Getting familiar with the statistical procedures Textbook examples: We have examples from popular textbooks and worked them out using R. Going further Frequently Asked Questions: We have a list of frequently asked questions (FAQs) regarding R. The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California.

FlowingData | Data Visualization, Infographics, and Statistics jxcore·io Home Page ProjectTemplate Electron Machine Learning Repository Google's R Style Guide R is a high-level programming language used primarily for statistical computing and graphics. The goal of the R Programming Style Guide is to make our R code easier to read, share, and verify. The rules below were designed in collaboration with the entire R user community at Google. Summary: R Style Rules File Names: end in .R Identifiers: (or variableName), FunctionName, kConstantName Line Length: maximum 80 characters Indentation: two spaces, no tabs Spacing Curly Braces: first on same line, last on own line else: Surround else with braces Assignment: use <-, not = Semicolons: don't use them General Layout and Ordering Commenting Guidelines: all comments begin with # followed by a space; inline comments need two spaces before the # Function Definitions and Calls Function Documentation Example Function TODO Style: TODO(username) Summary: R Language Rules Notation and Naming File Names File names should end in .R and, of course, be meaningful. Identifiers Syntax Spacing

numbers Numbers - an advanced mathematics toolkit for JavaScript and Node.js. Description Numbers provides a comprehensive set of mathematical tools that currently are not offered in JavaScript. Basic calculationsCalculusMatrix OperationsPrime NumbersStatisticsMore... A few things to note before using: JavaScript, like many languages, does not necessarily manage floating points as well as we'd all like it to. The primary uses cases are client side operations which the DOM will recognize (e.g. 1.1px == 1px). How to use Numbers is pretty straightforward to use. With node, simply require it: var numbers = require'numbers'; For example, if we wanted to estimate the integral of sin(x) from -2 to 4, we could: Use Riemann integrals (with 200 subdivisions) numberscalculusRiemannMathsin -2 4 200; Or use adaptive simpson quadrature (with epsilon .0001) numberscalculusadaptiveSimpsonMathsin -2 4 0001; User-defined functions can be used too: var myFunc = function(x) { return 2*Math.pow(x,2) + 1; We can add two matrices

The R Project for Statistical Computing