chart-visualization
Generate charts: select type, extract data, render image.
npx skills add HezaoHezao/poirot --skill chart-visualization --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Chart Visualization ## Overview Transform data into visual charts. Intelligently select the most suitable chart type, extract parameters, and generate a chart image. > **Poirot note:** The original deer-flow skill uses a bundled > `scripts/generate.js` (Node.js + charting library). Poirot doesn't bundle > that script. Use `bash` with Python (`matplotlib`/`plotly`) as the rendering > engine instead. Install: `pip install matplotlib plotly`. ## Chart Selection Guide | Data Pattern | Recommended Chart | When | |---|---|---| | **Time Series** | Line / Area | Trends over time | | **Comparisons** | Bar / Column | Categorical comparison | | **Distribution** | Histogram / Boxplot | Frequency distribution | | **Part-to-Whole** | Pie / Treemap | Proportions | | **Relationships** | Scatter | Correlation | | **Flow** | Sankey | Flow between stages | | **Multi-dimensional** | Radar | Compare across dimensions | | **Process** | Funnel | Stage conversion | | **Hierarchy** | Org chart / Mind map | Tree structure | | **Geographic** | Map | Spatial data | ## Workflow ### 1. Select Chart Type Analyze the user's data features: - Time dimension? → Line/Area - Categories? → Bar/Column - Proportions? →
- Overview
- Chart Selection Guide
- Workflow
- 1. Select Chart Type
- 2. Prepare Data
- 3. Generate Chart
- Common Chart Types via matplotlib
- Pitfalls
python3 -c "
import matplotlib
import matplotlib.pyplot as plt
labels = ['Jan', 'Feb', 'Mar', 'Apr', 'May']
values = [120, 150, 180, 200, 220]
Bar chart
import matplotlib; matplotlib.use('Agg')
cats = ['A', 'B', 'C', 'D']
vals = [23, 45, 12, 67]
Scatter plotWhat does the chart-visualization skill do?
Generate charts: select type, extract data, render image.
How do I install it?
Run `npx skills add HezaoHezao/poirot --skill chart-visualization --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From HezaoHezao/poirot, a repository with 139 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.