amarvenu/stanford-econ-programming-resources

A repo to crowdsource useful programming resources

Crowd sourcing programming resouces for Stanford economists

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.

Github

• Intro to Github
• How to make your first contribution.
• How to make your first contribution w/ Github desktop
• Atlassian's git guide

Stata

• Jack Blundell Stata intro
• Using "inlist()". A useful tool that will save you LOTS of time when defining variables.
• How to make (pretty) maps

Python

• 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
• Introduction to data visualization in Python

R

• [R for economists] (https://libguides.bates.edu/r/r-for-economics)

Matlab

• MathWorks. A website that contains many solutions to any coding issues you may face on Matlab.
• Tips for Matlab

Programming for economists

• Code and Data for the Social Sciences:A Practitioner's Guide (Gentzkow,Shapiro)
• Course on computation (Fernández-Villaverde)

R

• R for Data Science (Grolemund and Wickham)

General programming

• 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.
• StackOverflow. Online forum where people ask and answer coding questions. Insanely useful!

Docker (next level)

• Intro, why its good for econ/data science, and how to get started
• Docker Data Science Stack