We have Great Expectations for Pandas Profiling | Great Expectations

Given that you are reading this post on greatexpectations.io, we assume you’re a Python Data Person (TM). As a Python Data Person (TM), you are probably familiar with Pandas. And as someone familiar with Pandas, we also believe you may already be familiar with Pandas Profiling, a fantastic open source library for, well, profiling your data set. We’ve collaborated with Simon Brugman, the core maintainer behind Pandas Profiling, to include a super handy “to Expectation Suite” method in the library, which turns your profiled report into a Great Expectations Expectation Suite that you can use to validate your data. If this all makes sense to you (or if you’ve been watching the original GitHub issue for a while) and you can’t wait to try it out, you can install the latest version of Pandas Profiling (version v2.11.0 at the time of writing this post) and hop over to the examples in the Pandas Profiling repo straight away to get started - otherwise, stick around and learn more about what exactly we’ve been up to!

This is a companion discussion topic for the original entry at https://greatexpectations.io/blog/pandas-profiling-integration/
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