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

Package details

MaintainerHarel Lustiger <[email protected]>
LicenseMIT + file LICENSE
URL https://github.com/tidylab/tidylab.dpa
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
tidylab/tidylab.dqa documentation built on June 21, 2019, 7 p.m.