The package contains classes for performing data quality assurance: 1. Profile the data with **DataQualityProfiler** to discover inconsistencies and other anomalies in the data. 2. Perform data cleansing activities (e.g. removing outliers, missing data interpolation) with **DataQualityOperations** to improve the data quality.
|Maintainer||Harel Lustiger <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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