User Guide#

This guide covers the key concepts and features of ChartBook, helping you build and maintain analytics pipelines effectively.

Core Concepts#

📖 Concepts

Understand the core terminology: Pipelines, Catalogs, ChartBooks, and ChartHub.

Core Concepts
📊 Pipelines

Learn how to structure and build analytics pipelines with ChartBook.

Pipelines
📈 Charts

Create and manage interactive charts with metadata and documentation.

Charts
🗃️ Dataframes

Organize and document your data sources with comprehensive metadata.

Dataframes
📚 Catalog Projects

Combine multiple pipelines into a unified catalog.

Catalog Projects
📊 Plotting

Create charts with automatic multi-format export.

Plotting
🎨 Chart Gallery

Interactive examples of all chart types using FRED economic data.

ChartBook Plotting Gallery

Additional Topics#

📓 Notebooks

Integrate Jupyter notebooks into your documentation.

Notebooks
✍️ MyST Markdown

Learn MyST Markdown syntax for writing documentation.

Writing with MyST Markdown

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:

  1. Installed ChartBook (see Getting Started)

  2. Basic knowledge of Python and pandas

  3. Familiarity with command-line tools

  4. Understanding of data analysis concepts

Getting Help#

As you work through the guide: