claude

Data Visualisation And Publishing

Create static and interactive data visualisations for reports, repos, and data storytelling. Purpose-organised inventory of 60+ validated open-source tools as a head start — static figures (Matplotlib, Seaborn, ggplot2), web charts (Chart.js, ECharts, Plotly.js, ApexCharts, Highcharts), high-perf (uPlot, Perspective, Lightweight Charts), bespoke (D3, Observable Plot, Vega/Vega-Lite, visx, Victory), Python/R apps (Bokeh, Dash, Altair, Streamlit, Gradio, Shiny, D-Tale, Briefer, Preswald), storytelling (Vizzu, VChart, vue-data-ui, SandDance), graphs (G6, sigma.js, Cytoscape, Gephi, Graphviz, GoJS, 3d-force-graph, Constellation), maps (deck.gl, react-map-gl, Leaflet, MapLibre, OpenLayers, folium, react-globe.gl), mobile (fl_chart, F2), BI (Superset, Metabase, Grafana, Kibana, Redash, Chartbrew), diagrams-as-code (Mermaid, PlantUML), domain-specific (Iris, QuantInvestStrats, XCharts, BizCharts, Tablesaw).

31 on GitHubby Daniel Rosehillv1.1.0MITupdated yesterdayData & Datasets
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Plugin data-visualisation-and-publishing from marketplace danielrosehill in danielrosehill/Claude-Code-Plugins. Commands read from the repo's manifest — today.

What it installs

Skills (4)

  • choose-tool

    Decision protocol for selecting the right data visualisation tool from the inventory based on output medium, data shape, runtime, and storytelling needs. Use when the user asks for a chart/graphic/dashboard but hasn't specified a library.

  • data-storytelling

    Design and build data-storytelling pieces — narrative-driven visualisations with annotations, animated transitions, and interactive elements. Use when the goal is persuasion or explanation, not just analysis.

  • setup-environment

    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.

  • tool-inventory

    Purpose-organised catalogue of validated data visualisation libraries, grouped by use case so a tool can be located quickly. Reference this at the start of any dataviz task to get a head start.

Slash commands (3)

  • /data-visualisation-and-publishing:dataviz-pick

    Pick the right visualisation tool from the curated inventory for a given dataviz task.

  • /data-visualisation-and-publishing:dataviz-setup

    Scaffold a data visualisation environment in the current directory using the chosen inventory tool.

  • /data-visualisation-and-publishing:dataviz-story

    Design and build a data-storytelling visualisation — narrative-driven, annotated, optionally animated or interactive.

View source on GitHub blog.danielrosehill.com

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