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visualization-builder

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Create effective, publication-ready data visualizations. Use when choosing chart types, designing presentation visuals, building dashboard charts, or applying visual design best practices to data output.

04-data-storytelling-visualization/visualization-builder/SKILL.md

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# Visualization Builder

# When to use
- Choosing the right chart type for a specific analytical message
- A chart exists but is cluttered, misleading, or failing to make the point
- Building a chart for an executive presentation that must work without verbal explanation
- Producing consistent, branded visualisations across a report or dashboard
- Creating accessible charts that work for colorblind viewers or screen readers

# Process
1. **Identify the message type** — classify the chart's purpose: comparison (bar), trend over time (line), composition / part-of-whole (stacked bar, pie only for 2–3 categories), distribution (histogram, box plot), or relationship (scatter). The message type determines the chart type. See `references/chart_selection_guide.md`.
2. **Select and load the data** — confirm the data is at the right grain for the chart. Aggregations (e.g., groupby month) should happen before plotting, not inside the chart library.
3. **Build the base chart** — use `scripts/chart_builder.py` with pre-set professional styling (whitegrid, sans-serif, accessible color palette). Set axes, ticks, and scale deliberately — default settings are often wrong.
4. **Apply visual hierarchy** — make the most important data element visually dominant (bolder line, darker bar, distinct color). De-emphasise secondary series. Remove every element that doesn't contribute to the message (gridlines at 0.2 alpha, no top/right spines). See `references/visual_design_principles.md`.
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