I was pleased to represent Fred Hutch in late January at rstudio::conf2020 in San Francisco. In addition to having used RStudio as my interface for R statistical programming for the last several years, I’ve long admired the company’s commitment to open-source software and education. To that end, the workshop materials are publicly available on GitHub, and videos of all talks will eventually be available on RStudio’s resources page. If you’re interested in what other people thought about the conference, I also highly recommend the Twitter feed!
My own presentation focused on community building among researchers interested in developing their R coding skills, so I attended most of the conference sessions focused on education. Here are some of the projects I found most exciting:
- Teacups, Giraffes, and Statistics is a great way to learn statistics with beautiful art and narration
- TidyBlocks is a Scratch-like method of graphical programming based in TidyVerse
- Jeff Leek described an amazing effort to make data science an accessible career path for members of the community around Johns Hopkins; check out his slides: Using Data Science to Create Economic Opportunities in Baltimore
- R para Ciencia de Datos is a community developed Spanish translation of R for Data Science
There were multiple awesome sessions focusing on data visualization principles and tools. Here are some highlights:
- rayshader: a package for rendering high-quality 2D and 3D plots (especially maps)
- gifski: not new, but a useful package that can create gifs in R, used by other packages like gganimate
- Color and font: Practical Typography is a quick read on typesetting, and ColorBrewer can help with color theory. A little knowledge can go a long way towards improving your visualizations!
- Rmarkdown is increasingly popular for creating reproducible reports in a variety of deliverables (html, pdf, etc). There are lots of themes available, and you can view a gallery here.
- Resist the temptation to condense as much as possible into your designs. Reduce clutter, and add whitespace and line breaks to make them more visually appealing.
These presentations are more technical, but may be of interest to folks at the Hutch:
- Jenny Bryan’s keynote on debugging has loads of useful information! GitHub, video
- Technical debt is a social issue
- Simplified Data Quality Monitoring of Dynamic Longitudinal Data: A Functional Programming Approach
- R for Graphical Clinical Trial Reporting