Poor data quality can cause major problems for data teams, from disrupting pipelines to losing consumer trust. Many teams struggle with this, especially when data comes from upstream workflows outside their control.

The solution: data contracts. They document expectations, establish ownership, and enforce constraints within CI/CD workflows.

This practical book introduces data contract architecture, explains why the industry needs it, and shares real-world production use cases. You’ll learn to implement components and build a case for adoption in your organization.

Standard DataFrame output can feel clunky and unfinished. Without clean headers, readable dates, or currency formatting, even great data can look unprofessional.

Great Tables elevates your DataFrames into polished tables built for reports, dashboards, and presentations, all through one chainable interface.

Key features:

• Number formatting: currency, dates, compact notation
• Visual enhancements: mini charts, color gradients, embedded images
• Table structure: headers, subtitles, column control
• Multi-format export: PNG, PDF, HTML

Great Tables: Build Publication-Ready Tables in Python

Foundation model for tabular data with zero-shot classification and regression capabilities

Survival analysis built on top of scikit-learn for time-to-event prediction

Python library for fuzzy matching, record deduplication and entity resolution using machine learning