Loading...
Loading...
Found 257 Skills
Implement Syncfusion React Sparkline components for compact, inline data visualization. Use this when working with sparklines, mini charts, or trend indicators in constrained spaces. This skill covers all 5 sparkline types (line, column, area, win-loss, pie), tooltips, markers, data labels, range bands, axis customization, and themes. Ideal for displaying data trends within grids, dashboards, or tables without full-sized charts.
GitHub repository analytics dashboard — stars, forks, contributors, issues, pull requests, recent activity, and top contributors. Use when the brief asks for a GitHub repo dashboard, open-source growth report, repository health page, or GitHub analytics view.
Build a live MotherDuck dashboard as a Dive. Use when composing one shareable KPI, trend, and breakdown story over existing MotherDuck data, especially when the result should stay a saved workspace artifact rather than a full application.
Build ETL pipelines and analytics dashboards using Harvard Art Museums API with SQL and Streamlit
Implements Syncfusion .NET MAUI TreeMap (SfTreeMap) for visualizing hierarchical data with rectangles sized and colored by values. Use when implementing hierarchical data visualization, heat maps, squarified layouts, multi-level data grouping, or brush settings for hierarchical displays. This skill covers installation, data binding, layout types, hierarchical levels with GroupPath, legend configuration, tooltips, and TreeMap customization.
9 diagrams & visuals skills. Trigger: creating diagrams, flowcharts, architecture visuals, LaTeX drawings. Design: tool-specific guides (Mermaid, Excalidraw, TikZ) with academic conventions.
Use when working with Lightdash YAML files, dbt models with Lightdash metadata, the lightdash CLI (deploy, upload, download, preview, lint, warehouse-catalog, sql, set-warehouse), or managing charts, dashboards, spaces and access, AI agents, scheduled content, users, groups, custom roles, metrics, and dimensions as code
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
Expert business intelligence covering dashboard design, data visualization, reporting automation, and executive insights delivery.
A high-level interactive graphing library for Python. Ideal for web-based visualizations, 3D plots, and complex interactive dashboards. Built on plotly.js, it allows users to zoom, pan, and hover over data points in a browser-based environment. Use for interactive charts, web applications, Jupyter notebooks, 3D data visualization, geographic maps, financial charts, animations, time-series analysis, and building production-ready dashboards with Dash.
Create interactive chart visualizations (bar, line, pie) from data.
Use when asked to create publication-ready scientific figures, charts for research papers, or academic visualizations.