From exploratory analysis to shareable outputs
Analysis isn't complete until it's communicated. This session covers how to move from exploratory notebooks to polished outputs that stakeholders can actually use—interactive dashboards, PDF reports, and web pages.
Different audiences need different formats. This session covers three approaches:
For audiences who want to explore the data themselves. Streamlit turns Python scripts into interactive web applications with minimal code. Users can filter, select, and drill down into your analysis.
Best for: Technical colleagues, data teams, iterative exploration
For audiences who need polished, printable documents. PDF generation from notebooks or markdown creates professional reports that work offline and maintain consistent formatting.
Best for: Executives, board presentations, archival records
For audiences who need persistent, shareable links. Static pages hosted on GitHub Pages provide a stable URL for your findings that anyone can access without special software.
Best for: Public communication, sharing with external stakeholders
Details are in your module template repository. The session guides you through:
You'll learn to think about audience needs before choosing output format— a skill as important as the technical implementation.