pandera is a project that provides a flexible and expressive API for performing data validation on dataframe-like objects to make data processing pipelines more readable and robust.
Dataframes contain information that pandera explicitly validates at runtime. This is useful in production-critical or reproducible research settings.
pandera is free and open source software.
Features include:
- Define a schema once and use it to validate different dataframe types including pandas, dask, modin, and pyspark.
- Check the types and properties of columns in a DataFrame or values in a Series.
- Perform more complex statistical validation like hypothesis testing.
- Seamlessly integrate with existing data analysis/processing pipelines via function decorators.
- Define dataframe models with the class-based API with pydantic-style syntax and validate dataframes using the typing syntax.
- Synthesize data from schema objects for property-based testing with pandas data structures.
- Lazily Validate dataframes so that all validation checks are executed before raising an error.
Integrate with a rich ecosystem of python tools like pydantic, fastapi, and mypy.
Website: www.union.ai/pandera
Support: GitHub Code Repository
Developer: Niels Bantilan
License: MIT License
pandera is written in Python. Learn Python with our recommended free books and free tutorials.
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