Taking control of animations in R and demystifying them in the process
“During this post I will go in depth with how it is possible to make very fancy and custom animations in R.”
How to make an RMarkdown Website
“By the end of this (hopefully) you will have, constructed a simple website with basic information about yourself, hosted it to github for the world to access, have enough knowledge to know what to google to make it better.”
Neural Networks from Scratch (in R)
“This post is for those of you with a statistics/econometrics background but not necessarily a machine-learning one and for those of you who want some guidance in building a neural-network from scratch in R to better understand how everything fits (and how it doesn’t).”
rrtools: Tools for Writing Reproducible Research in R
‘The goal of rrtools is to provide instructions, templates, and functions for making a basic compendium suitable for doing reproducible research with R. This package documents the key steps and provides convenient functions for quickly creating a new research compendium.”
A gRadual intRoduction to the tidyverse
“This is a workshop for the Cascadia-R conference meant to be a gentle introduction to the tidyverse for data wrangling and visualization.”
Novel Approaches to First Statistics / Data Science Course
“Presentations and supplementary materials for the Novel Approaches to First Statistics / Data Science Course at JSM 2017.”
Interactive flow visualization in R
“Over the past couple years, R developers have created an infrastructure to bridge R with JavaScript using the htmlwidgets package, allowing for the generation of interactive web visualizations straight from R. I’d like to demonstrate here a few examples for exploratory interactive flow graphics that use this infrastructure.”
RStudio
“Before we can start exploring data in R, there are some key concepts to understand first: What are R and RStudio? How do I code in R? What are R packages?”
Visualising Residuals
This post will cover various methods for visualising residuals from regression-based models.
Data Paintings (The kandinsky Package)
“Recently I have moaned about not really knowing what I was doing with the grid package (see here and here). I’m happy to say, not only did I take the time to better understand the grid package, I also wrote my own package around it – the kandinsky package! To generate random Wassily Kandinsky paintings or even make any dataset into one. You’re probably wondering what on earth am I talking about. If you’re not interested in my ramblings just go to the package itself.”
These are just some of the links Mara shares each day. Her curation of resources is a remarkable contribution to a community of practice. She has transformed my understanding of the scope and depth within one topic in my open online Sport Informatics and Analytics Wikieducator course.
I am delighted I have a Mastodon account (@KeithLyons). It provides a 500 character space for each toot.
