From data-visualisation-and-publishing
Stand up a working data visualisation environment in a repo or workspace — install deps, create a starter project, wire up a reproducible build. Use after a tool has been chosen and the user needs it ready to run.
npx claudepluginhub danielrosehill/claude-code-plugins --plugin data-visualisation-and-publishingThis skill uses the workspace's default tool permissions.
Use this after `skills/choose-tool` has selected a library. The goal is a minimal, reproducible environment the user can iterate in.
Mandates invoking relevant skills via tools before any response in coding sessions. Covers access, priorities, and adaptations for Claude Code, Copilot CLI, Gemini CLI.
Share bugs, ideas, or general feedback.
Use this after skills/choose-tool has selected a library. The goal is a minimal, reproducible environment the user can iterate in.
data/, generated output under output/ (or dist/), source under src/.project/
├── pyproject.toml # or requirements.txt
├── data/
├── src/
│ └── plots.py
├── output/
└── README.md
uv or venv to isolate.matplotlib, pandas, numpy; add bokeh or dash/plotly as needed.kaleido (Plotly) or use Bokeh's export_png (requires selenium/chromedriver or Playwright).project/
├── package.json
├── index.html
├── src/
│ └── chart.(js|ts|jsx|tsx)
└── data/
dist/ and host as static assets.flutter create, add fl_chart to pubspec.yaml, pin a version.pip install.conda/mamba (it has non-trivial geospatial C deps); document the conda env.If the target is data storytelling (narrative scrolling, animated transitions):
narrative/ folder for Markdown/MDX copy alongside the chart code so the story and viz stay together.Always leave the user with:
python src/plots.py or npm run build).