tidylab/tidylab.dqa: Data Quality Assurance Activities for Inconsistencies Discovery and Data Cleansing
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.
Getting started
Browse package contents
Package details |
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| Maintainer | Harel Lustiger <tidylab@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.19.25 |
| URL | https://github.com/tidylab/tidylab.dpa |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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