Here are some of the best IDEs for R programming that can help in complex data analysis and provide an easy to navigate UI. Also listed are some lightweight online R compilers to help you work on the go.
Install R in Ubuntu: A Complete Guide to Setting up R Development Environment - LinuxForDevices
In this guide, we'll learn to install R in Ubuntu. R is an open-source programming language used extensively for statistical and scientific computing. Due to
Shell vs R Fundamentals – From Syntax to Control Structures with Zsh & BASH
Overview This walkthrough of the fundamentals of shell programming with Z shell (Zsh) and Bourne Again SHell (BASH) includes a comparison of similar components and features in R and RStudio. An alt…
Tiny things can separate life into “before” and “after”. Here is one. For almost a year I’ve been daily sending mental “thank you” to Ugo (@ugobas) who showed me how to re-organize panes in RStudio. Since then I’ve been spreading this tiny improvement so many times that I thought the tiny advise deserved a separate tiny post. Please note, below is an opinionated view of a comfortable UI improvement; feel free to ignore it if you don’t like. This advise is highly subjective, though, I really believe it is useful.
getsysreqs/get-sysreqs.R at main · mdneuzerling/getsysreqs
Determine system requirements from R packages using the RStudio Package Manager. This is a weekend project, not a real package, so please think twice before using it for anything serious. - getsys...
Locking down R package dependencies and versions is a solved problem, thanks to the easy-to-use renv package. System dependencies — those Linux packages that need to be installed to make certain R packages work — are a bit harder to manage. Option 1: Hard-coding The easiest option is to hard-code the system dependencies. I did this recently when I was creating a Dockerfile for a very simple Plumber API: RUN apt-get update -qq && apt-get -y --no-install-recommends install \ make \ libsodium-dev \ libicu-dev \ libcurl4-openssl-dev \ libssl-dev My Dockerfile used only three R packages and so its system dependencies were not complicated.
Practical Advice for R in Production - Answering Your Questions
This is a guest post by Colin Gillespie from Jumping Rivers answering your questions from their most recent series of webinars, Practical Advice for Putting R in Production.
Debugging in R: How to Easily and Efficiently Conquer Errors in Your Code
When you write code, you’re sure to run into problems from time to time. Here are some advanced tips and tricks for handling these errors, explained accessibly.
In this article we present our R package rsync, which serves as an interface between R and the popular Linux command line tool rsync. Rsync allows users of Unix systems to synchronize local and remote files between two locations.
Introduction Starting the viewer Sorting Filtering Searching Advanced topics Auto-refreshing Labels Restrictions and Performance Saving filters Introduction RStudio includes a data viewer th...
20 Free Online Books to Learn R and Data Science - Python and R Tips
If you are interested in learning Data Science with R, but not interested in spending money on books, you are definitely in a very good space. There are a number of fantastic R/Data Science books and resources available online for free from top most creators and scientists. Here are such 13 free 20 free (so […]
Customizing Package Build Options – RStudio Support
Customizing Package Build Options Overview There are three R package build commands used by the RStudio package development tools: R CMD check R CMD build R CMD INSTALL It's possible to c...
Overview Code snippets are text macros that are used for quickly inserting common snippets of code. For example, the fun snippet inserts an R function definition: If you select the snippet from th...
RStudio IDE Easy Tricks You Might've Missed · R Views
The RStudio IDE reached version 1.0 this month. The IDE has come a long way since the initial release 5 and a half years ago. Many major features have been built: projects, package building tools, notebooks. During that same period, often hidden in the shadows, a growing list of smaller features has been changing lives. In celebration of version 1.0 this post hopes to spread fanfare for a few of these easy-to-miss tools.
Recommended Packages Many useful R function come in packages, free libraries of code written by R's active user community. To install an R package, open an R session and type at the command line in...
HTTPS to Secure Your RStudio Shiny App Work Environment
HTTPS to Secure Your RStudio + Shiny App Work Environment Click any link in list below to jump to topic Creating a Friendly URL Route 53 to Host Domain and Create Subdomains AWS Certificate Manager for SSL keys AWS Elastic Load Balancers: HTTPS Redirection Installing Nginx & Creating Configuration Files I wanted to create this post as an addition to my previous post Running R on AWS EC2 and Logging into RStudio from Anywhere to show how to secure your AWS environment.
Package management: Using repositories in production systems | R-bloggers
Data science is characterized among other things using open source tools. An advantage when working with open source languages such as R or Python is the large package world. This provides tools for numerous use cases and problems through the development within huge communities. The packages are organized in digital ...
pins: Pin, Discover and Share Resources | RStudio Blog
Today we are excited to announce the pins package is available on CRAN! pins allows you to pin, discover and share remote resources, locally or in remote storage. If you find yourself using download.file() or asking others to download files before running your R code, use pin() to achieve fast, simple and reliable reproducible research over remote resources. Pins You can use the pins package to: Pin remote resources locally to work offline and cache results with ease, pin() stores resources in boards which you can then retrieve with pin_get().
RStudio's webinars offer helpful perspective and advice to data scientists, data science leaders, DevOps engineers and IT Admins. Presenters come from companies around the globe, as well as the RStudio staff.
15 new ideas and new tools for R gathered from the RStudio Conference 2019
Below we list the tools and innovations from the RStudio Conference in Austin, Texas that we found the most useful and exciting. As with last year’s conference, the event is well organized an…