This repository is a hub of assorted resources compiled to help ARE students learn to program for Economics in open source software, principally R and python. The organization of this repository is as follows;
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Stata to opensource is a pair of tutorials that go through common data cleaning and manipulation exercises that one might do in Stata in both R and python. For now this tutorial is limited to data analysis; in the future, topics on regression analysis and exporting to LaTeX will be added.
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Installation_guides has two guides to installing and using python:
- Anaconda: This is the recommended tutorial that installs python and the jupyter notebook and spyder IDEs via miniconda.
- python-alone: Not recommended. Installs python directly and teaches how to run python in the terminal and to write python code in plain text editors.
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The topics folder is a catch-all for topical tutorials focused on students in ARE 212. For now, it includes only:
- A short introduction to list comprehensions in python
- A guide to branching, pull requests, and code review in github.
For a guide to computing and coding resources available on campus to CNR students, check out this document (berkeley.edu email required to view).
A huge thanks to Simon Greenhill and Connor Jackson for their contributions to files in this repository and to Berkeley ARE for supporting this work.