Charts

This skill provides comprehensive guidance for creating, organizing, and managing Helm charts for Kubernetes application packaging. It includes step-by-step workflows for chart structure, templating patterns, multi-environment configuration, and a validation script to ensure chart quality and security best practices.

This skill provides comprehensive guidance for using Plotly, a Python library for creating interactive, publication-quality data visualizations. It covers 40+ chart types including scatter plots, bar charts, 3D surfaces, and geographic maps, along with styling, export options, and Dash integration for web applications.

This skill provides expert guidance on using matplotlib for data visualization in Python. It covers both pyplot and object-oriented interfaces, includes comprehensive reference documentation for plot types, styling, and troubleshooting, plus ready-to-use template scripts for creating publication-quality figures.

Mviz is a data visualization skill that generates clean, professional charts and dashboards from compact JSON specifications or markdown files. It supports 17+ chart types (bar, line, scatter, heatmap, sankey, etc.) and 8 UI components, using a 16-column grid layout system with light/dark theme support.

Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.

A comprehensive guide for creating interactive data visualizations using D3.js. Provides detailed code patterns for bar charts, line charts, scatter plots, heatmaps, chord diagrams, force-directed networks, geographic maps, and hierarchical visualizations, along with reference materials for color schemes, scales, and responsive design.