Data Visualization

Data Visualization Skill (Plotly-first)

Create clear, accurate, readable charts with Plotly. Prefer lean visuals, correct layout, and no overlapping text.

When to Use

• Analytical charts for reports or exploration
• Choosing the right chart for a dataset and question
• Exporting SVG/PNG figures for documents
• Fixing unreadable charts (overlap, clipping, bad sizing)

When Not to Use

• Comparisons already clear in a small table
• Mermaid / architecture diagrams (technical-reporting)
• Interactive Dash apps (plotly-dash)
• Pure statistical computation (data-science)

Related Skills

• Use data-science when metrics still need to be computed.
• Use technical-reporting when embedding figures into a saved markdown file.
• Use data-storytelling when the chart supports a stakeholder decision (numbers must already be validated).

Core Principles

1. Choose chart by purpose, not by habit.
2. Prefer fewer labels over complete labels.
3. Optimize layout for readability before styling.
4. Never deliver a chart with overlapping or clipped text.
5. If exact values matter more than shape, use a table.
6. Keep in-chart text short; put long explanation outside the visual.

Chart Selection

If categories are many or names are long → prefer horizontal bar.

Plotly Defaults

• Plotly Express for simple charts; Graph Objects when fine control is needed.
• Set explicit width and height for content density.
• Enable automargin: fig.update_xaxes(automargin=True) and fig.update_yaxes(automargin=True).
• Keep legend off the data area when possible.
• Use consistent units and clear axis titles.

Anti-Overlap Rules

• Do not label every point by default.
• Label only key points: top-N, outliers, or highlighted series.
• For dense labels, alternate textposition, thin ticks, or rely on hover.
• Rotate or shorten ticks when categories collide.
• If still colliding: (1) reduce label count, (2) modestly increase figure size, (3) keep only 1–3 annotations.
• Never "solve" overlap by making font unreadable.

Layout & Export

• Leave margin for title, ticks, legend, annotations.
• Prefer one message per chart.
• SVG export requires Kaleido. Pass size on export, e.g. fig.write_image("chart.svg", width=900, height=560).
• Prefer SVG for report-quality vector output.
• Visually inspect the exported file before delivery.

Visual QA Checklist

• Chart type matches purpose
• Table considered when exact values matter more
• In-chart text is short and necessary
• No overlapping labels/ticks/legend
• No clipped text or overflow
• Width/height fit content; Kaleido used for SVG
• Readable at final display size
• Long explanation moved outside the figure