User Guide#
This guide covers the key concepts and features of ChartBook, helping you build and maintain analytics pipelines effectively.
Core Concepts#
Understand the core terminology: Pipelines, Catalogs, ChartBooks, and ChartHub.
Learn how to structure and build analytics pipelines with ChartBook.
Create and manage interactive charts with metadata and documentation.
Organize and document your data sources with comprehensive metadata.
Combine multiple pipelines into a unified catalog.
Create charts with automatic multi-format export.
Interactive examples of all chart types using FRED economic data.
Additional Topics#
Integrate Jupyter notebooks into your documentation.
Learn MyST Markdown syntax for writing documentation.
What You’ll Learn#
Pipeline Architecture: How to structure reproducible analytics pipelines
Data Management: Best practices for organizing and documenting data
Chart Creation: Building interactive visualizations with proper metadata
Documentation: Generating beautiful, searchable documentation websites
Deployment: Publishing and sharing your analytics
Prerequisites#
Before diving into the user guide, make sure you have:
Installed ChartBook (see Getting Started)
Basic knowledge of Python and pandas
Familiarity with command-line tools
Understanding of data analysis concepts
Getting Help#
As you work through the guide:
Check the Examples for practical demonstrations
Refer to the API Reference for detailed API documentation
Use the CLI Reference for command-line options