Prompting GPT-4: Streamlit and Folium are a Match Made for Mapping
Author(s): John Loewen, PhD
Originally published on Towards AI.
UN GPI data visuals with Python’s streamlit-folium library
Dall-E image: impressionist painting of multi-visual dashboard as a mural on a building
It’s just nuts how much prompt engineering with GPT-4 can speed up the Python coding process for complex data visualizations.
Just recently, I figured out how to leverage GPT-4 to implement interactive data visualizations using the Python folium library and the Streamlit framework.
Why is this a big deal? Let me explain:
Folium is a fantastic Python library that allows you to create beautiful maps. You can choose map layers and legends and all kinds of cool functionality.Streamlit is a Python framework that is used to create fully functional interactive dashboards. For example, users can choose options from a dropdown menu to display associated maps and charts.streamlit-folium is a library that allows you to integrate folium maps into a Streamlit dashboard — and GPT-4 can auto-create this code for you!
I know! This is a super-cool development — GPT-4 can now write working Python code for your cross-framework workflow.
Let‘s use a cool data set to step through this together and I’ll show you how it works!
Today, let’s find a data set that gives us information about which countries are relatively safe to visit these days. We can go and dig around on… Read the full blog for free on Medium.
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Note: Article content contains the views of the contributing authors and not Towards AI.
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