Practical Techniques for Polished Visuals with Plotnine
summary
Builds an area chart of coal production since 1900 from the Carbon Majors dataset, computes the first year >100M tons and places datadriven annotations and vertical guide lines. Uses plotnine layers for custom axes, fills by commodity, and scale_fill_manual with a six‑color palette, then calls P.draw to perform a plotnine → matplotlib conversion and adds colored inline labels via highlight_text; code, slides and data links are published and reproducible.
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chapters (13)
- 0:00Introduction
- 1:05What is Plotnine
- 4:24Preparing data
- 6:56Reusable color and font
- 10:44First chart layer
- 13:09Customizing axes
- 15:20Data-driven annotations
- 17:11Area chart colors
- 19:20Theme and legend
- 21:32Highlight annotations
- 24:48Finalizing visualization
- 25:08Summary
- 26:34Q&A Plotnine vs others
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