This is a repo to crowdsource useful programming resources and to learn how to use GitHub in the process. If you want to add a link to the list, then please submit a pull request. You can also propose changes to how we structure the document (either in the issues list or in a pull request). Any other thoughts, then create an issue.
- Intro to Github
- How to make your first contribution.
- How to make your first contribution w/ Github desktop
- Atlassian's git guide
- How to make (pretty) maps
- Jack Blundell Stata intro
- Using "inlist()". A useful tool that will save you LOTS of time when defining variables.
- Stata Forum
- QuantEcon. A website with many examples of economic models being solved with Python (and Julia too!).
- Cheetsheet by Quantecon for Python; Python vs Matlab vs Julia; Stats: Python pandas vs Stata vs R.
- Introduction to Scientific Computing with Python (CME 193). A one-unit course at Stanford -- worth taking at some point to see the full capacity of Python.
- Stata to Python Cheatsheet
- Geeks for Geeks Tutorial on web scraping with Beautiful Soup.
- Introduction to data visualization in Python
- MathWorks. A website that contains many solutions to any coding issues you may face on Matlab.
- Tips for Matlab
- R4DataScience. Free online textbook guiding you how to use R for data science purposes.
- R for Data Science (Grolemund and Wickham)
- R for economists
- A collection of charts in R
- Code and Data for the Social Sciences:A Practitioner's Guide (Gentzkow,Shapiro)
- Course on computation (Fernández-Villaverde)
- Toward Data Science. Short articles on all things Python. Want to know how to use some of the packages listed above? There is bound to be an intro here.
- QuantEcon Notes
- StackOverflow. Online forum where people ask and answer coding questions. Insanely useful!