Plotly Express's choropleth is one of the cleanest "low-code, high-output" data viz tools in the Python ecosystem, but the documentation skips a few non-obvious gotchas that bite you the first time you build a US-state-level map. This walkthrough builds a publication-grade state map end-to-end, using a real dataset I open-sourced last week. The dataset: the most-searched fragrance in every US state over the last 12 months, pulled from Google Trends across 30 of the most-talked-about fragrances of 2024-2026. Full dataset on GitHub under CC BY 4.0 , full written analysis at perfumem.com . What you'll build A US state choropleth where each state is colored by its category winner (a discrete, not continuous, value), with a clean legend and a high-DPI export that's safe to drop into a blog post or report. Setup pip install plotly pandas kaleido Enter fullscreen mode Exit fullscreen mode kaleido is the static image export engine; you need it if you want PNG output instead of just an interactive HTML chart.…