Instructor Michael Cullan introduces the how and the why of presenting results in data science. We covered some common tools and techniques for sharing interactive reports and conducting reproducible research.
Michael showed us the steps to:
- Clean up an exploratory Jupyter notebook into a presentable report
- Set up a Github repository to share notebooks and software requirements
- Create a new git branch to update a notebook without modifying the master copy
- Distribute a report in an interactive form using Binder
Additional Notes: If you would like to follow along on your own machine, there are a few steps to take care of. If you don’t already have a Github account, make sure you create one. You should also ensure you have a Python distribution with conda and Jupyter and that you’ve installed Github’s command line tool.