With the continuing rise in popularity of Data Science and the integration of R into the Microsoft ecosystem it´s time to bring together several articles on R from 2016.
This is done to give you the benefits of a focused guide to the essentials of R and a little bit more.
It is most useful for developers and those wanting to get started in data science.
Chapter 1 - An Overview Of R
The first article looked at R from the ground up, highlighting it´s roots, what it can do for you, some things you should know about R and a few resources which include
- R is regarded as a challenging language to learn
- There are R conferences around the world
- R is good for presentations
Chapter 2 - Good Tutorials
The second article brought together a list of tutorials suitable for different audiences, including ones for Shiny and R Markdown. These included
- R Introduction at Data Camp for Data Science
- R Tutorial for Programmers
- Academic statistics approach to R
Chapter 3 - Setting up Your Environment
Every coder needs somewhere to build their code and the third article looks at some of the options for R. Other options were also given but the main 3 were:
Chapter 4 - Some Useful Commands
The fourth article looks at a few common things to look out for, how to get help, data wrangling and commands for stats.
Chapter 5 - Getting Involved in Packages
The fifth article highlights the importance of Packages to R and details of how to install them and where to find them
- List of Packages at CRAN
- Packages list for data from R Studio
- Packages for data import, wrangling and visualisation
Chapter 6 - Best Practices of R
Every programming language has its best practices, and the sixth article looks at the how and why of this, considering styles and R specifics
- R Style Guide at Google
- Advanced R Style Guide from Hadley Wickham
- Consistent Naming Conventions in R
Chapter 7 - Entering the Hadleyverse
The final chapter delves into the world of packages and contributions by Hadley Wickham. Noted highlights include
There are a lot of R resources included here, so get started and let us know any great resources we´ve missed!