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Found 6 Skills
Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.
Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.
Data visualization for charts and graphs. Use when user needs "画图/图表/可视化". Creates static PNG or interactive HTML charts from data.
Build PyGraphistry visualizations with bindings, encodings, layout controls, static export, and privacy-aware sharing. Use for color/size/icon/badge styling, layout tuning, map/static output, and plot link sharing workflows.
Create production-quality data visualizations including charts, dashboards, and infographics. Use when the user asks to visualize data, create charts, build dashboards, make infographics, plot statistics, or transform datasets into visual representations. Supports React/Recharts artifacts, static images (PNG/PDF via Python), and interactive HTML. Triggers include "visualize this data", "create a chart", "build a dashboard", "make a graph", "plot this", "infographic", or any request to represent data visually.
Use when "data visualization", "plotting", "charts", "matplotlib", "plotly", "seaborn", "graphs", "figures", "heatmap", "scatter plot", "bar chart", "interactive plots"