Protect your data and ML products from low-quality data

The open-source framework for precision data testing for data scientists and ML engineers.

Pandera: The open-source framework for precision data testing

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Build confidence in the quality of your data by defining schemas for complex data objects

Pandera provides a simple, flexible and extensible data-testing framework for validating not only your data, but also the functions that produce them.

Don’t take our word for it — take theirs!

Moderna Therapeutics

On our team, we’re using Pandera in every project that touches pandas DataFrames. As a programming tool, it lets us automatically check our DataFrames at runtime and in unit tests. As a tool for thought, it forces clarity on the purpose of DataFrames that we use and make in our projects.

Eric Ma, Moderna
Eric J. Ma
Principal Data Scientist, Moderna Therapeutics
Dendra Systems

Our data changes frequently, and we want a way to easily maintain and update our expectations about what counts as valid data. We use Pandera as a very fancy assertion statement to catch data errors in all the nodes of our production pipelines. Since we’ve adopted it, Pandera has helped us maintain the quality of our code during development and the quality of our models in production.

Richard Decal,
Richard Decal
Senior ML Engineer, Dendra Systems
Cox Automotive

Before Pandera, I had trouble with validating the data that I was pulling in from various databases. Pandera has saved me numerous times from the consequences of using poor-quality data. When Pandera data checks determine that something is incorrect, I can react quickly to resolve the situation or send a note out to my internal customers. Thanks a lot, Niels and the Pandera team, for such a great tool!

John Kang, Cox Automotive
John Kang
Director, Cox Automotive

Pandera is a great data-validation toolkit! It's fast, extensible and easy to use. The community behind it is very helpful and responsive. Pandera is a must for data-intensive applications.

Ayazhan Zhakhan,
Ayazhan Zhakhan

A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness

Write Complex Schemas with Ease

Write Complex Schemas with Ease

Leverage Pandera’s zero-configuration API for defining schemas using modern Pythonic idioms.

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Validate Critical Points of Your Pipeline

Validate Critical Points of Your Pipeline

Identify the critical points in your data pipeline, and validate data going in and out of them.

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Quickly Bootstrap Schemas with Trusted Data

Quickly Bootstrap Schemas with Trusted Data

Overcome the initial hurdle of defining a schema by inferring one from clean data, then refine it over time.

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Easily Create Custom Validation Checks

Easily Create Custom Validation Checks

Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases.

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Synthesize Fake Data to Validate Pipelines

Synthesize Fake Data to Validate Pipelines

Validate the functions that produce your data by automatically generating test cases for them.

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Check Out the Documentation

Integrate seamlessly with the Python ecosystem

Supported Data Frameworks


Supported Integrations


Supported Orchestrators

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