# Paperchart Grouped Bar

> Render vertical bars arranged in groups for side-by-side categorical comparison. Use when each category has two or three values that deserve equal visual weight, for example "theoretical feasibility versus observed traffic", "model A versus model B across benchmarks", or "before versus after versus projection". Not for part-to-whole data.

- Skill: `shuakami/paperchart-grouped-bar` (Agent Skill)
- Install (CLI): `npx skillmds@latest add shuakami/paperchart-grouped-bar`
- Raw SKILL.md: https://api.skillmd.com/api/skills/shuakami/paperchart-grouped-bar/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: MIT
- Author: shuakami (https://skillmd.com/u/shuakami)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/shuakami/paperchart-grouped-bar

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# paperchart — grouped bar

Vertical bars grouped by category. Each category gets N bars side by side (one per series). Useful for paired or triple comparisons where each series matters on its own and the reader wants to compare heights directly.

## When to use

- Two or three series across five to eight categories.
- Any time bars should be read in absolute terms, not normalised.
- Avoid if series values span many orders of magnitude — prefer `slope` or `latency` (log scale).

## Input shape

```json
{
  "data": {
    "series": [
      { "key": "theoretical", "label": "theoretically feasible" },
      { "key": "observed",    "label": "observed in traffic" }
    ],
    "groups": [
      { "label": "computer & math", "values": { "theoretical": 94, "observed": 33 } },
      { "label": "office & admin",  "values": { "theoretical": 90, "observed": 22 } }
    ]
  }
}
```

## Visual rules

- Accent colour on the first series, secondary on the second.
- Value labels above every bar; x labels below each group.
- Five gridlines at 0 / 25 / 50 / 75 / 100 of `yMax`.