plotly-interactive-visualization
Interactive visualization with Plotly. 40+ chart types (scatter, line, heatmap, 3D, geographic) with hover, zoom, pan. Two APIs: Plotly Express (DataFrame) and Graph Objects (fine control). For static publication figures use matplotlib; for statistical grammar use seaborn.
npx skills add BioTender-max/awesome-bio-agent-skills --skill plotly-interactive-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.
# Plotly — Interactive Scientific Visualization ## Overview Plotly is a Python graphing library for interactive, web-embeddable visualizations with 40+ chart types. It provides two APIs: Plotly Express (high-level, pandas-native) for quick plots and Graph Objects (low-level) for full customization. Output to interactive HTML, static PNG/PDF/SVG, or Dash web apps. ## When to Use - Creating interactive charts with hover tooltips, zoom, and pan - Building multi-panel exploratory dashboards for data analysis - Visualizing 3D data (surfaces, scatter3d, mesh, volume) - Making geographic/map visualizations (choropleth, scatter_geo) - Presenting data in web-embeddable HTML format - Statistical distribution comparison (violin, box, histogram with marginals) - Time series with range sliders and animation frames - For **static publication-quality figures** (journal submissions), use `matplotlib` instead - For **statistical grammar-of-graphics** style, use `seaborn` instead ## Prerequisites - **Python packages**: `plotly`, `pandas`, `numpy` - **For static export**: `kaleido` (PNG/PDF/SVG rendering) - **For web apps**: `dash` (optional) ```bash pip install plotly kaleido ``` ## Quick Start ```p
- Overview
- When to Use
- Prerequisites
- Quick Start
- Core API
- 1. Plotly Express (High-Level API)
- 2. Graph Objects (Low-Level API)
- 3. Subplots and Multi-Panel Layouts
- 4. Statistical Charts
- 5. Export and Rendering
- 6. Interactivity Features
- Common Workflows
- Workflow 1: Exploratory Data Analysis Dashboard
- Workflow 2: Publication Figure with Annotations
pip install plotly kaleido
What does the plotly-interactive-visualization skill do?
Interactive visualization with Plotly. 40+ chart types (scatter, line, heatmap, 3D, geographic) with hover, zoom, pan. Two APIs: Plotly Express (DataFrame) and Graph Objects (fine control). For static publication figures use matplotlib; for statistical grammar use seaborn.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill plotly-interactive-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 BioTender-max/awesome-bio-agent-skills, a repository with 144 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.