Jupyter notebooks provide a useful environment for interactive exploration of data. A common question, though, is how you can progress from this nonlinear, interactive, trial-and-error style of analysis to a more linear and reproducible analysis based on organized, well-tested code. This series of videos shows an example of how I approach reproducible data analysis within the Jupyter notebook.
Each video is approximately 5-8 minutes; the videos are listed in the Jupyter Notebook linked above. Alternatively, you can view the playlist directly on YouTube.