Create interactive and static charts using Plotly Express and Graph Objects.
npx skills add https://github.com/biomaps-infra/blender-opencode --skill lib-plotly
Please help me install this Agent Skill. Skill: lib-plotly Source: https://github.com/biomaps-infra/blender-opencode/tree/main/.opencode/skills/lib-plotly Command: npx skills add https://github.com/biomaps-infra/blender-opencode --skill lib-plotly
This Skill empowers users to create a wide range of interactive, web-embeddable data visualizations, making complex data accessible and understandable for analysis, dashboards, and presentations.
Use the lib-plotly skill to create a scatter plot from the provided dataframe with 'x' on the x-axis and 'y' on the y-axis.
High-intent search queries and answers about installing and using this skill.
You can create interactive charts for dashboards using over 40 visualization types, featuring hover info, zoom, and pan capabilities. Both high-level Plotly Express and low-level Graph Objects APIs are supported to build web-embeddable graphics.
You can generate over 40 publication-quality chart types for statistical analysis and data exploration, ranging from basic scatter plots to complex 3D and hierarchical visualizations. These interactive graphics facilitate comprehensive data exploration.
Yes, interactive graphics can be exported to static image formats including PNG, PDF, and SVG for publications. This allows you to transition from exploratory data analysis to print-ready presentation outputs.
Yes, the library supports complex multi-plot layouts and time series visualization. You can build intricate dashboards and interactive presentations by combining multiple chart components within a single figure.
High-level APIs like Plotly Express provide simplified syntax for rapid chart creation, while low-level Graph Objects APIs offer fine-grained control over interactive graphics. Both approaches produce web-embeddable visualizations suitable for dashboards.
Yes, Python is required as this is a Python library for creating interactive visualizations. You use Python dataframes and scripts to generate the charts, which can then be embedded into web applications or exported as static images.
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