This repository contains a collection of resources for doing data analysis in Python. It is developed for the course Physics 201: Data Analysis for Physicists at Harvard, but it may be useful to others doing applied Bayesian inference in the physical sciences and engineering.
- Getting started guide: installing and running your Python data-analysis tools
- Environment files for use with conda/mamba
- Docker images (TBD)
- Wiki and FAQ
Notebooks, code, and other files are released under the GNU General Public License v3. Copyright belongs to the authors specified in each file. If not specified, the material is Copyright (C) Vinothan N. Manoharan 2022.
The wiki is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.