popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets. popmon creates histograms of features binned in time-slices, and compares the stability of the profiles and distributions of those histograms using statistical tests, both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher-dimensional, e.g. it can also track correlations between any two features. popmon can automatically flag and alert on changes observed over time, such as trends, shifts, peaks, outliers, anomalies, changing correlations, etc, using monitoring business rules. Advanced users can leverage popmon's modular data pipeline to customize their workflow. Visualization of the pipeline can be useful when debugging or for didactic purposes. There is a script included with the package that you can use.

Features

  • Reports and integrations
  • Comparison and profile extensions
  • Popmon currently integrates with Diptest
  • Resources on how to integrate popmon are available in the examples directory
  • External libraries or custom functionality can be easily added to Profiles and Comparisons
  • Python/C++ implementation of Hartigan & Hartigan's dip test for unimodality

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Categories

Data Profiling

License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Data Profiling Tool

Registered

2023-06-12