In the last few years I've created a number of "Data Apps" in Python using the Streamlit framework. The most recent one was the Immigration Enforcement app I shared here a few weeks ago (link).
In my experience tools like this are normally used by people who work in tech. That is, analytical types who work with public data tend not to use them.
I feel like this is a missed opportunity, because Streamlit is an excellent tool for helping people understand datasets. And public datasets are probably the most important datasets around.
With that in mind, I just published a free tutorial on how to create Data Apps in Python With Streamlit.
The course does have some technical prerequisites: I think it would be hard to finish without having at least some prior experience with both the terminal / command line and git.
If this interests you, and you have that experience, I encourage you to give the course a try. It's structured as a github repo with:
- a demo app
- instructions on how to run the demo app
- a light tutorial on how the demo app works
- exercises for improving the app. These exercises are tasks I regularly do while working with Streamlit. I think this is where most of the learning will occur.
- instructions on how to deploy the finished app so that you can share it with friends and family.
If this interests you, you can take the course here: https://github.com/arilamstein/streamlit_tutorial?tab=readme-ov-file#streamlit_tutorial
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Ari Lamstein
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