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From Boring to Beautiful: How I Used Claude to Transform a Dash App in Minutes


I've been learning Python data visualisation, working through Murat Durmus's Hands-On Introduction to Essential Python Libraries and Frameworks alongside the official Dash tutorial. The resulting code was functional — a basic bar chart comparing data for San Francisco and Montréal — but it looked like exactly what it was: a beginner's first attempt. Plain white background, default colours, numbered axes, and a title that just said "Data Viz."

So I decided to run an experiment. Could Claude AI turn a scrappy 20-line script into something genuinely worth showing people?


Before running the prompt


The First Prompt

I pasted the code into Claude.ai with a simple instruction: "Rewrite this following code to be graphically more interesting."

The result was striking. Claude switched to a dark "neon terminal" aesthetic — deep navy background, electric teal and magenta accents, and a stylish monospaced font. The bars got proper labels, the axes were cleaned up, and the whole thing felt intentional rather than accidental. It had gone from looking like homework to looking like a developer portfolio piece.


After the 1st prompt



Refining for a Real Audience

I pushed further. Same code, new prompt: "Rewrite this to be graphically more interesting for a general audience. Choose whatever works best for this audience."


After the second prompt



This time Claude made very different choices — and that's the interesting part. Recognising that a general audience needs warmth and clarity rather than technical cool, it switched to a bright, friendly design. Rounded bars in coral and teal, a clean white card layout, and a Nunito font that feels approachable rather than intimidating. It even added summary stat cards above the chart — showing the average and peak month for each city — so someone who doesn't want to "read" a chart can still instantly understand the data.

What I Noticed

The code grew substantially. My original 20 lines became well over 150 — defining colour palettes, layout styles, hover tooltips, and summary components. That might sound like more complexity, but it's actually the opposite: Claude generated the boilerplate so I didn't have to. The finished app is more readable for users, even if there's more code underneath.

The bigger lesson? The prompt matters as much as the tool. "More interesting" and "more interesting for a general audience" produced completely different results — one optimised for aesthetics, one for usability.


 

Code based on dash.plotly.com/tutorial and Murat Durmus (2023), pages 143–145.

 

References

Anthropic. (2024). Claude AI [Large language model]. Retrieved from https://claude.ai

Durmus, M. (2023). Hands-on introduction to essential Python libraries and frameworks (pp. 143–145). Amazon KDP. Retrieved from https://www.amazon.com

Plotly Technologies Inc. (2024). Dash documentation: Tutorial. Retrieved from https://dash.plotly.com/tutorial

All opinions in this blog are the Author's and should not in any way be seen as reflecting the views of any organisation the Author has any association with. Twitter @scottturneruon
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