Cookbook for R alyssa frazee Thu 02 January 2014 | -- (permalink) My sister is a senior undergraduate majoring in sociology. She just landed an awesome analyst job for next semester and was told she'll be using some R in the course of her work. She asked me to show her the ropes during winter vacation, and of course I said yes! One catch: the day we planned to work, it turned out we only had an hour of overlapping free time. Challenge accepted. (1) download R and RStudio I'm impressed that RStudio is both accessible/helpful for beginners and useful for experts. (2) console and script The first thing we did after getting set up was type two lines into the console: It wasn't exactly "hello world", but it illustrated some concepts like "assignment" and "variables" and "evaluation"2. The next thing I had my sister do was save those two lines of code in an R script. (3) comments # COMMENTS ARE SUPER IMPORTANT so we learned about them (4) graphics x = rnorm(1000, mean = 100, sd = 3) hist(x) (5) getting help (6) data types vectors
· R Tools for Visual Studio Welcome to R Tools for Visual Studio Preview! About this release THANK YOU for trying out this second preview release of R Tools for Visual Studio (RTVS)! We welcome your feedback and comments; we’re actively monitoring our Github issue tracker and triage new incoming issues every Friday. Of course, we remind you that this release is meant for evaluation purposes only and not for production use. If you already have VS2015 with Update 1 (or higher) installed and R installed, you can download RTVS from the link below - but we highly recommend following the Installation guide: Download R Tools for Visual Studio Meet the RTVS Engineering Team in New York City on May 12! Are you in the NYC area on May 12th? If interested, please sign up here. Key features in Version 0.3 For an overview of what is new in 0.3, please see our What’s New in 0.3 page. Completely New Features for 0.3 Existing and Improved Features A quick video overview Installation and first steps The pre-requisites for RTVS are: Q. A. Q. A.
R Moves Up From #9 to #6, But What Does It Mean to Really be Proficient in a Language? There's been a lot of noise in the data science community this past week about IEEE Spectrum's 2015 language rankings, where R moved up three notches from #9 in 2014 to #6 in 2015. The Spectrum post gives some lip service to needing to know a domain in addition to just the language itself. But here I drill down into what it means to really know a language. API for the standard library. So, do you really know R?
Inicio LIBROS RECOMENDADOS PARA APRENDER ESTADÍSTICA CON R - Blog Estadística & R Hoy vengo con una lista de libros recomendados para leer en cualquier momento de tu carrera profesional porque son algunos de los mejores y más leídos libros de Estadística con R. Todos los libros que te enseño son excelentes, no hay un orden de importancia, pero sí hay diferencias en la complejidad de cada uno. Voy a comentarte cada libro para que sepas si está hecho para ti. Es un curso de Estadística básica con R que logra su objective, es rápido y una buena referencia para comenzar. Libro de R básico que se divide en pequeños pasos orientados a la realización de tareas. Es una introducción al lenguaje R y cómo utilizarlo para el análisis estadístico y gráfico. R for Beginners de Emmanuel Paradis The R Book de Michael J. Una guía extensa sobre la estadística aplicada en R, puedes encontrar de todo en este libraco. A first course in statistical programming with R de W.J. Es una buena introducción para emperzar a programar en R. A Beginner´s Guide to R de Alan Zuur Muy bueno.
R Commander John Fox and Milan Bouchet-Valat Please Read the Rcmdr Installation Notes (click on the image for a larger view) For more details, see my paper on the R Commander in the Journal of Statistical Software (which is somewhat out of date) and the introductory manual distributed with the package (accessible via the Help -> Introduction to the R Commander menu). The R-Commander GUI consists of a window containing several menus, buttons, and information fields. (The menu tree, etc., are shown below.) The menus lead to simple dialog boxes, the general contents of which are more or less obvious from the names of the menu items. By default, commands generated via the dialogs are posted to the output window, along with printed output, and to the script window. Commands access a current or active data set (data frame). In addition to standard packages, the R Commander uses functions in a number of other packages. I'm making the GUI available as the Rcmdr package.
bookdown: Easy Book Publishing with R Markdown R for Data Science Learn R : 12 Free Books and Online Resources – YOU CANalytics Please read the disclaimer about the Free PDF Books in this article at the bottom R, an open-source statistical and data mining programming language, is slowly but surely catching up in its race with commercial software like SAS & SPSS. I believe R will eventually replace SAS as the language of choice for modeling and analysis for most organizations. The primary reason for this is plainly commercial. Most organizations are questioning the heavy annual cost of SAS on their P&L statement. This is escalated with the presence of R as a free and viable replacement. Human Obsession with Linearity – by Roopam Non-Linear Self-Learning Humans are obsessed with linearity. Learning / teaching in schools and universities usually take the linear path, however, self-learning, in my opinion, is highly non-linear. 1. First of all, thanks to Jared for recommending this book in the comments section of this article. Read the Full Book: R for Data Science Read Full PDF: R in Action Read Full PDF: The R Book 2.
Translated Syntax, Curriculum, Quantitative Analysis Center Understanding Syntax The Passion Driven Statistics curriculum is intended to help students perform basic data management and statistical tests across 4 major statistical software platforms (R, SAS, Stata and SPSS). This web page provides a library of basic commands that the user can copy and paste into R, SAS, Stata or SPSS to perform a variety data management tasks and basic statistical tests. Our goal is to help student’s use statistical computing as a building block in scientific reasoning and creativity. Rather than producing students who can think about statistics from a software-specific perspective, these resources are meant to help students move flexibly and confidently between statistical software environments. It is important to note that we use the following convention when presenting software-specific syntax. Contents needed for every program Calling in a data set Sorting the data Abbreviating a data set to a smaller number of variables (i.e. columns) Data management tasks
Writing an R package from scratch Anyone who has created their own R package has probably come across Hilary Parker’s awesome blogpost, that walks you through creating your very first R package. The comprehensive detail on everything R packages can be found in Hadley Wickham’s superb book. In this post I am going to walk through some of the developments in the package development space since Hilary wrote her blog four years ago, in particular focussing on the relatively recent usethis package. I’ve made the assumption for this following tutorial that you’re a sane individual and that you’re using the RStudio IDE. My main motivation stemmed from Hadley’s tweet: The package I have created during the course of this blog can be found on my GitHub. Initial Setup Within this section we will assemble the bare bones of a package and is very similar to Hilary’s blog I linked to earlier. Step 0: Packages we need The three packages we require are devtools, roxygen2 and usethis. Step 1: Creating the package create_package("dogs") install()