Research Guides
Reproducibility: Coding Basics
Open Source Programming
Open source programming languages are ideal for reproducible research because scripts can be written that preserve all the activity. The choice of language is personal, but it’s easier if you chose a language that others in your field are already using. You can then use a development environment as your coding interface. Finally, you should find appropriate libraries, which function as pre-made code shortcuts.
Python
Many researchers in the physical sciences use Python. Python is a general-purpose programming language, and so can be applicable for a wider range of tasks beyond data analysis; it is also much easier to integrate Python scripts into outside systems like web apps or production databases. Some consider it easier to learn than R because of its clear syntax.
Python Resources
Online:
- CodeCademy PythonA great online tutorial for learning python
- Coursera PythonAn excellent, free online MOOC
At UW:
- eScience Institute Office HoursData Scientists at UW's eScience Institute can help with Python questions
R
Many researchers in the biological and social sciences use R, which has a large library of diverse statistical package support. R is great for manipulating large tables of data and running analyses that others have coded.
R Resources
Online:
- RStudio Online LearningLinks to beginning R tutorials
- Coursera RA free, online MOOC
- rOpenSci's Reproducibility in Science GuiderOpenSci's general reproducibility guide for those working in R
At UW:
- eScience Institute Office HoursMany researchers associated with the eScience Institute use R, and are able to answer questions.
- Center for Social Science Computation and ResearchCSSCR offers courses in RStudio, open to all UW students