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Found 136 Skills
Generate publication-ready scientific figures in Python/matplotlib with a consistent figures4papers house style. Use when creating or refining academic bar/trend/heatmap/scatter/multi-panel figures, enforcing visual consistency, or exporting paper-ready PNG/PDF/SVG outputs.
Plotly Chart Generator - Auto-activating skill for Visual Content. Triggers on: plotly chart generator, plotly chart generator Part of the Visual Content skill category.
Use this skill when designing presentations, slide decks, or pitch materials. Triggers on "create a presentation", "design slides", "build a deck", "structure my talk", "make a pitch deck", "data visualization for slides", or any request involving slide layout, storytelling frameworks (Pyramid Principle, Hero's Journey, Problem-Solution-Benefit), narrative arc, speaker notes, or chart selection for presentations. Covers slide structure, visual hierarchy, data-driven storytelling, and deck architecture from executive summaries to conference keynotes.
Comprehensive guide for AntV L7 geospatial visualization library. Use when users need to: (1) Create interactive maps with WebGL rendering (2) Visualize geographic data (points, lines, polygons, heatmaps) (3) Build location-based data dashboards (4) Add map layers, interactions, or animations (5) Process and display GeoJSON, CSV, or other spatial data (6) Integrate maps with AMap (GaodeMap), Mapbox, Maplibre, or standalone L7 Map (7) Optimize performance for large-scale geographic datasets
Fetch, store, and visualize GitHub repository traffic data (views, clones, referrers, stars) with trend charts. Requires repo push access.
Assemble multi-panel scientific figures with panel labels (A, B, C) at publication quality (300 DPI) using R. Use when combining individual plots into journal-ready figures.
Visualize relationships between two variables. Use for correlation analysis and pattern identification.
Visualize competitive positioning using sector charts. Use for market analysis and competitive strategy.
Analyze Walmart sales data to explore trends between store sales and unemployment rates. Generate insightful visualizations and a beautiful HTML report with deep analysis. Suitable for quick insights into the relationship between sales data and macroeconomic factors.
This skill should be used when users need to analyze CSV or Excel files, understand data patterns, generate statistical summaries, or create data visualizations. Trigger keywords include "analyze CSV", "analyze Excel", "data analysis", "CSV analysis", "Excel analysis", "data statistics", "generate charts", "data visualization", "分析CSV", "分析Excel", "数据分析", "CSV分析", "Excel分析", "数据统计", "生成图表", "数据可视化".
Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.
Common style patterns, layer configurations, and recipes for typical mapping scenarios including restaurant finders, real estate, data visualization, navigation, and more. Use when implementing specific map use cases or looking for proven style patterns.