Additional Learning Resources
1 General
- Wilson, Greg, Jennifer Bryan, Karen Cranston, Justin Kitzes, Lex Nederbragt, and Tracy K. Teal. 2017. “Good Enough Practices in Scientific Computing.” PLOS Computational Biology 13 (6): e1005510. https://doi.org/10.1371/journal.pcbi.1005510
- Best Practices when Writing Code by Daniel M. Sullivan
- Data science for economists by Grant McDermott
2 R
2.1 General
- R for Reproducible Scientific Analysis by Software Carpentry
- R for Data Science (2e) by Hadley Wickham et al.
2.2 Beginner
- Learn R by Codecademy
- Hands-On Programming with R by Garrett Grolemund
2.3 Intermediate/Advanced
- NCEAS Learning Hub’s coreR Course
- Advanced R by Hadley Wickham
- Efficient R programming by Colin Gillespie
2.4 Visualization
- Data Visualization: A Practical Introduction by Kieran Healy
- ggplot2: Elegant Graphics for Data Analysis (3e) by Hadley Wickham et al.
2.5 GIS
- Geocomputation with R by Robin Lovelace et al.
- Geographic Data Science with R: Visualizing and Analyzing Environmental Change by Michael Wimberly
- Spatial Data Science by Edzer Pebesma and Roger Bivand
- RFF GIS Learning Lab
3 Python
- The Python Tutorial
- Python Datascience Handbook by Jake VanderPlas
- Data Science from Scratch by Joel Grus
- Automate the Boring Stuff with Python by Al Sweigart
- Plotting and Programming in Python by Software Carpentry
- Python Web Scraping: Full Tutorial With Examples (2025) by Kevin Sahin
- Fluent Python by Luciano Ramalho
4 Julia
- Julia Manual
- Julia Academy
- Julia Data Science by Jose Storopoli et al
- Getting Started · DataFrames.jl
- Tutorial · Plots
- Julia Performance Tips
5 Stata
6 MATLAB
- MATLAB Onramp Course
- MATLAB: A Practical Approach by Stormy Attaway
- Numerical Methods using MATLAB by George Lindfield and John Penny