R Weekly Training

Warning This repo is currently undergoing a rewrite. Please wait until this warning disappears before using the materials herein.

Welcome to the DfE R Community's R Weekly Training! This programme should get you up-to-speed with the basics of R. This programme is run annually over a 3(ish)-month period, so if you're interested in participating but aren't sure when the next round will be, get in touch 🙂

Scope

What this programme is:

A collection of questions, broken down by topic, with links to good resources to help you complete them
A way of learning by doing, with an emphasis on doing your own research and getting review from other colleagues

What this programme isn't:

A detailed guide on how to use R, RStudio or R packages

The programme has been designed this way because maintaining learning materials requires a sustained focus which most organisations don't have resource for. As a result, organisation-internal learning materials tend to become obsolete as the organisation moves on to new and better ways of doing things, or, if the organisation doesn't move on, they hold them back from adopting better ways of working. For this reason, this programme simply aims to point you to resources which are widely used and frequently updated, encouraging you to develop the habits you need to stay abreast of changes to technologies and best practice. In other words, while other programmes may give you a fish, this programme aims to give you a fishing pole, and to point you to the lake.

Get Started

Each week has its own subdirectory in this repo. The exercises for each week are given in the README.md file for that week, meaning they should be nicely rendered when viewed online in GitHub (or Azure DevOps). These folders may also contain other resources, e.g. datasets, to make use of when completing the exercises. To get started, go to Week 01.

Some things we'll cover

Data wrangling using dplyr and tidyr
Data visualisation using ggplot2
Text manipulation using regular expressions and stringr
Functional programming using purrr
App/dashboard development using shiny
The basics report generation using R Markdown
Good coding practice using the tidyverse style guide
The basics of version control using Git and GitHub

Resources

For DfE colleagues, the DfE R Community Training Support channel on Teams is a good place to ask for help if you get stuck on a problem
R for Data Science is a great, free e-book by Hadley Wickham, from which this programme liberally borrows
RStudio Cheatsheets are a great way to quickly brush-up on specific R packages

Contact