| author | editor | license |
|---|---|---|
John Little |
source |
CC BY-NC |
-blue "DOI"){kind=icon}
This repo supports preparation for remote zoom-based teaching. I'm flipping the workshop.
R and the Tidyverse are a data-first coding language that enables reproducible workflows. In this two-part workshop, you'll learn the fundamentals of R, everything you need to know to quickly get started.
I recommend installing R and RStudio (how-to video) on your local machine. There are cloud versions of RStudio that will work. The cloud version has some very minor differences that, in my experience, are monumental differences for beginners. Therefore I recommend installing the R/RStudio locally if possible. Anyway, I think the flexibility of a local install outweighs the minor convenience of a cloud instance. I will not cover the differences in the workshop. Still another way is to use the cloud copy of this github repo by launching the binder.org button (above) -- You may need to be very patient while the launch configuration initiates (2-20 minutes. YMMV.)
The quickstart.qmd (or _output/quickstart.html) represents the general outline of the flipped workshop -- i.e. what we can reasonably cover in two 2-hour workshops (videos available.) In fact, the quickstart.qmd file is the basic guide I follow when people sign-up for my workshops. Meanwhile the outline.qmd (or _output/outline.qmd) file represents the grand overview of how to reach Tidy data fluency with R (book forthcoming). You can find an HTML report of the outline in the _output directory. I serve these files out of github because I want you to immediately start using practical reproducible approaches and I want you to have the code locally. A book is great and I recommend many in the outline, but my goal is to get you working with code, today.
This is a two-part workshop. In Part 1 you'll learn the fundamentals of R, everything you need to know to quickly get started. You'll learn how to wrangle data for analysis, gain a brief introduction to visualization, practice Exploratory Data Analysis (EDA), and how to generate reports. In Part 2 you'll learn about visualization using ggplot2, how to make interactive charts for use in dashboards, how to reshape and merge data, and be introduced to models.
No prerequisites and no prior experience is necessary. By the end of part 1 you will import data, edit and save scripts, subset data, use projects to organize your work, and develop self-help techniques.
- quickstart.qmd
- ggplot_quick.qmd
- longer_wider.qmd
- regression.qmd
For access to videos, see the Rfun quickStart with R page.
There are URLs in the outline and quickstart files (and elsewhere). Among those links you can find links to various static and interactive exercises. And, I have a useful set of exercises at the intro2r-code github repo.