Have you ever worked with a dataset so rich, so multidimensional, that no single graph—or even a dashboard—could do it justice?
That was the challenge I kept running into as a data scientist and educator. Whether I was exploring US Census trends or trying to make immigration enforcement data more transparent, I found myself wishing for a better way to let others explore the data, not just look at my summary.
Enter: Streamlit—a Python framework that lets you build interactive web apps without writing a single line of front-end code.
Next week, I’m teaching a hands-on workshop with the American Statistical Association (ASA) and Instats.org called Data Apps in Python with Streamlit. It’s designed for researchers, analysts, and educators who are comfortable with Python and want to learn how to turn their analyses into simple, shareable apps.
What You’ll Learn
Across two focused sessions—three hours on Monday and three hours on Tuesday—we’ll walk through the full lifecycle of building and deploying a data app.
This workshop includes a review of Python’s data analysis ecosystem using Jupyter Notebooks and Pandas. After this review you’ll learn how to:
- Move from Jupyter Notebooks to a polished app
- Visualize data dynamically with Pandas and Plotly
- Use Streamlit widgets to create interactive filters and controls
- Structure your project for clarity and reproducibility
- Use GitHub and uv to manage your environment and deploy with confidence
- Integrate Microsoft Copilot or other LLMs to support your coding workflow
You’ll build a working app that visualizes trends in US Census data—but the skills you’ll learn are transferable to any dataset or research question. The final app you deploy will have its own URL which you can share with colleagues, friends, and family, and will look like this:
Why This Workshop?
If you’ve ever:
- Wanted to share your analysis with collaborators or students in a more engaging way
- Struggled to summarize a complex dataset in a static figure
- Wondered how to make your Python projects more reproducible and user-friendly
…this course is for you.
No prior experience with Streamlit or web development is required. If you’ve worked with Python before—even just a little—you’ll be able to follow along. We’ll review key tools like Pandas, Jupyter Notebooks, and GitHub as part of the workshop, so passing familiarity is plenty. And if you have a dataset you’re curious about, even better—but we’ll provide examples you can build on, so you don’t need to bring anything to participate fully.
Join Me
The course runs October 27–28, with two live Zoom sessions—just three hours each day—plus 30-day access to all materials and a monitored Q&A forum. You’ll also receive an official certificate of completion.
Let’s build something interactive together!
