Overview
Most AI-generated visualization code produces a chart that looks like a default matplotlib output from 2012: gray background, default colors, no styling, axis labels that say "x" and "y". It answers the question "does this code run?" but not "does this chart communicate effectively?" The gap between runnable code and production-quality code is entirely in the styling, annotation, and structural decisions that most code generators skip.
Production visualization code has three requirements beyond correctness: it is reusable (parameterized, not hardcoded), it is styled (publication-quality, not default), and it is documented (the chart's purpose is clear from the code). Code that meets only the first requirement produces charts that work but don't communicate.
The Python Data Visualization Code Generator Prompt generates complete, production-ready Python visualization code: library selection by chart type and use case, full styling specification, reusable function structure, and inline documentation that explains every non-obvious decision.
What you get: - Library selection with rationale (matplotlib/seaborn/Plotly/Altair) - Complete, runnable code with production styling - Reusable function structure with parameters - Inline documentation for non-obvious decisions - Export specification for multiple output formats
Built for: data scientists, analysts, and ML engineers who need visualization code that is immediately usable in production reports, notebooks, and dashboards.