editrules: Parsing, Applying, and Manipulating Data Cleaning Rules

Please note: active development has moved to packages 'validate' and 'errorlocate'. Facilitates reading and manipulating (multivariate) data restrictions (edit rules) on numerical and categorical data. Rules can be defined with common R syntax and parsed to an internal (matrix-like format). Rules can be manipulated with variable elimination and value substitution methods, allowing for feasibility checks and more. Data can be tested against the rules and erroneous fields can be found based on Fellegi and Holt's generalized principle. Rules dependencies can be visualized with using the 'igraph' package.

Version:	2.9.5
Depends:	R (≥ 2.12.0), igraph
Imports:	lpSolveAPI
Suggests:	testthat
Published:	2024-05-04
DOI:	10.32614/CRAN.package.editrules
Author:	Edwin de Jonge, Mark van der Loo
Maintainer:	Edwin de Jonge <edwindjonge at gmail.com>
BugReports:	https://github.com/data-cleaning/editrules/issues
License:	GPL-3
URL:	https://github.com/data-cleaning/editrules
NeedsCompilation:	no
Materials:	NEWS
In views:	OfficialStatistics
CRAN checks:	editrules results

Documentation:

Reference manual:	editrules.pdf
Vignettes:	editrules-vignette

Downloads:

Package source:	editrules_2.9.5.tar.gz
Windows binaries:	r-devel: editrules_2.9.5.zip, r-release: editrules_2.9.5.zip, r-oldrel: editrules_2.9.5.zip
macOS binaries:	r-release (arm64): editrules_2.9.5.tgz, r-oldrel (arm64): editrules_2.9.5.tgz, r-release (x86_64): editrules_2.9.5.tgz, r-oldrel (x86_64): editrules_2.9.5.tgz
Old sources:	editrules archive

Reverse dependencies:

Reverse depends:	deducorrect
Reverse suggests:	rspa

Linking:

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