Teaching R with Pokémon Go data

tl;dr

I wrote and delivered a basic intro to R and RStudio for some colleagues of mine.

You teach me and I’ll teach you

I wrote in a recent post about some training materials I wrote for teaching R Markdown.

Now I’m sharing another thing I made: Beginner R and RStudio Training (featuring Pokémon!). It’s an introduction to R, RStudio, R Projects, directory structure and the tidyverse. It uses Pokémon Go¹ data that I collected myself.²

You can:

• visit the page where the training is hosted
• look at the source on GitHub
• access a ‘follow along’ R script prepared by a colleague

It’s pretty rudimentary in content and design but it got the job done. I’m unlikely to update it any time soon. Feel free to use all of it, parts of it, or even fork it on GitHub and improve it.

Other materials

Why didn’t I just use materials that are already out there? Well, I find it easier to teach material that I know well and that’s particularly true for things I’ve written myself. Also I couldn’t find any Pokémon-themed guides, so it was obviously inevitable.

Below are some other training materials to consider. I’m certain some of these will be out of date over time, or better things will emerge, but I’m unlikely to come back and update this post in the meantime.

Starting with R and RStudio

• Software Carpentry’s Programming with R
• Swirl teaches you R interactively, from within RStudio itself
• Further information about R Projects is available from the RStudio Support pages
• Starting data analysis/wrangling with R: Things I wish I’d been told by Stian Håklev
• Basics of ‘tidy’ data and the ‘tidyverse’ of packages

Going further

• Data wrangling, exploration, and analysis with R from STAT 545 at the Uni of British Columbia
• Online learning from RStudio: R Programming, Shiny, R Markdown and Data Science
• An exhaustive Quora question with links to resources

Data Science in R

• An Introduction to Statistical and Data Sciences via R by ModernDive
• R for Data Science and exercise solutions

Getting help

• RStudio cheat sheets, including help with {readr}, {dplyr} and {ggplot2}
• Often it helps to produce a small reproducible example (a ‘reprex’) of your code if you run into trouble
• Getting help with R page of resources from RStudio
• Explore questions and answers tagged as r on StackOverflow

Environment

Session info

Last rendered: 2023-08-07 23:00:24 BST

R version 4.3.1 (2023-06-16)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.2.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Europe/London
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] htmlwidgets_1.6.2 compiler_4.3.1    fastmap_1.1.1     cli_3.6.1        
 [5] tools_4.3.1       htmltools_0.5.5   rstudioapi_0.15.0 yaml_2.3.7       
 [9] rmarkdown_2.23    knitr_1.43.1      jsonlite_1.8.7    xfun_0.39        
[13] digest_0.6.33     rlang_1.1.1       evaluate_0.21    

Footnotes

1. Add me as a friend on Pokémon Go. Friend code: 9572 6464 0472.

2. The data are available in my ‘draytasets’ GitHub repository and in the pkmn_go function in my {dray} package.

Reuse