Test-Driven Data Analysis
summary
Shows a concrete workflow: install tdda with pip, use reference tests to capture inputs and outputs and auto-update golden files, and run tdda discover/verify/detect on CSV or pandas data frames to generate JSON constraints and failing records. Demonstrates automatic constraint discovery (min/max, nulls, uniques, regexes), command‑line and API usage, and regex generation for identifiers; reports numbers of passing/failing constraints and writes failing rows so broken data or changed formats are actionable.
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chapters (9)
- 0:00Introduction
- 1:58Test-driven data analysis
- 9:25TDD ideas for data analysis
- 14:02Reference tests
- 38:26Real-world reference testing
- 44:08Constraints in analysis
- 1:04:24Advanced constraint features
- 1:11:25Rex PI for regex generation
- 1:20:32Q&A
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