Streamlining Interactive Maps with ChatGPT, Python and Plotly Dash

Prompt engineering interactive Python data visualizations

Final working maps using prompt engineering with Python dash and folium libraries

In the recent past, creating data visualizations, particularly in Python, was a finicky affair.

Not anymore.

In this article, two datasets, each organized by country and year, are compared to draw meaningful insights. A solution to display the data on two maps side-by-side, to allow comparison by year, is proposed. To solve this problem, prompt engineering with ChatGPT is used to efficiently generate interactive Python data visualizations in just 4 steps:

1. Find, clean, and convert the datasets
2. Generate a folium map
3. Generate dash App with dropdown menu to display folium map (by time period)
4. Generate a second map to display and hook it in to the Dropdown, update both maps with one selection

A modular approach like this is recommended as it gives us a return point to go back to if there are any problems.

So let’s get started…

STEP 1. Find, clean, convert.

What dataset should we use today? I don’t know about you, but I think coffee is awesome. It is warm, soothing, tasty…