Validating and Testing R Dataframes with Pandera via reticulate
summary
Shows that Pandera via reticulate validates R dataframes by calling Pandera schemas from R, using a conda env and reticulate to pass dataframes into Python and back. Demonstrates a DataFrameModel class, schema.validate lazy=True to collect all failures, and schema.example() to synthesize test data. Claims Pandera enforces types, ranges, regex and custom checks, reports precise failure rows, and the demo works end-to-end though not exhaustively across every R datatype.
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chapters (12)
- 0:00Data validation challenges
- 3:21Why validation matters
- 6:30Introducing Pandera
- 7:37Defining Pandera schemas
- 10:07Validating data and errors
- 12:40Validation in functions
- 14:08Advanced schema options
- 15:51Built-in and custom checks
- 17:14Regex for large datasets
- 18:40Pandera with R via reticulate
- 19:46Generating test data
- 20:49Summary and Q&A
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