Appendix B — Data and resources
This page contains links to the data we’re using in our workshop, and a sample of a few useful resources online and in print. This is by no means a comprehensive list, but it provides resources for continued learning. All of these examples provide code in same shape or form.
B.1 Datasets
This is a list of the data sources used in this workshop. For live-coding, please refer to this link, which will update everytime we save a file. That means you can refresh the page to see whatever code we are typing, and download this file at anytime.
- Full Dataset as a zipped folder. Inside you’ll find these files:
- Fisheries data: fishdat.csv
- Fisheries station locations: statloc.csv
- 2016 seagrass coverage shapefile:
- All R scripts used in the lessons as a zipped folder. Inside you’ll find these files:
B.2 Resources
B.2.1 TBEP Trainings
B.2.2 R Lessons & Tutorials
- DSOS/AEMON-J Hacking Limnology 2022, supporting open science workshops
- Software Carpentry: R for Reproducible Scientific Analysis
- Data Carpentry: Geospatial Workshop
- Data Carpentry: R for Data Analysis and Visualization of Ecological Data
- Data Carpentry: Data Organization in Spreadsheets
- Reproducible Reporting with R (R\(^3\)) for Marine Ecological Indicators
- R for Water Resources Data Science
- RStudio Webinars, many topics
- R For Cats: Basic introduction site, with cats!
- Topical cheatsheets from Posit, also viewed from the help menu
- Cheatsheet from CRAN of base R functions
- Totally awesome R-related artwork by Allison Horst
- Color reference PDF with text names, Color cheatsheet PDF from NCEAS
B.2.3 R eBooks/Courses
- Jenny Bryan’s Stat545.com
- Garrett Grolemund and Hadley Wickham’s R For Data Science
- Chester Ismay and Albert Y. Kim’s Modern DiveR
- Julia Silge and David Robinson Text Mining with R
- Hadley Wickham’s Advanced R
- Hadley Wickham’s R for Data Science
- Hadley Wickham’s R for Data Science, 2nd edition
- Hadley Wickham’s Mastering Shiny
- Yihui Xie R Markdown: The Definitive Guide
- Winston Chang R Graphics Cookbook
- Wegman et al. Remote Sensing and GIS for Ecologists: Using Open Source Software
- Lovelace et al. Geocomputation with R
- Edszer Pebesma and Roger Bivand Spatial Data Science