What you can expect to learn 🦾
Wrangling:Clean, transform and prepare data for analysis with dplyr, tidyr, stringr, lubridate, forcats, tibbleVisualization:Build static and interactive plots with ggplot2, plotly, ggiraph, tidygraph and learn to do animations using gganimate. Explore many ggplot2 extensions.Text analysis:Transform characters, words, sentences, pages and books into data with tidytext, regex and ggwordcloudReporting:Write reports with prose and data at the same time Quarto and learn how to manage references with Zotero️
Mapping:visualize geospatial data with sf, and go interactive with leaflet and spectacular with rayshaderData recovery:Import data from online sources and webpages with rvest, pdftools, readrPublishing:Create apps and dashboard with shiny. Build entire websites with quarto
Apply it to your own project đź’«
If you want, you can start your own project (a thesis, a blog, a paper, etc.) during the workshop.
The idea of this project is not to burden you with extra work, but to avoid that 6 months from now you’ll say “wait, that looks familiar but, of course, I didn’t use it for a while and now I can’t remember anything!”. All of these are practical and important tools for your work, and applying them to something you are already passionate about will let you keep all these lessons beyond your time working with us.
Extra content 🔥
If time allows, these are additional topics that we’ll cover with overly enthusiastic and committed students:
Iteration: You’ll learn to write better and shorter code with functional programming purrrModels: Learn how to build reproducible and tractable models with tidymodelsBayesian analysis: You need to unlearn a lot of what you were taught on statistics, but I’ll help you along and so will rethinking, rstanarm, bayesplot, brms and bayesrules