Package: editrules 2.9.3

Edwin de Jonge

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.

Authors:Edwin de Jonge, Mark van der Loo

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editrules.pdf |editrules.html✨
editrules/json (API)
NEWS

Peer review:

Bug tracker:https://github.com/data-cleaning/editrules/issues

On CRAN:

48 exports 20 stars 2.29 score 12 dependencies 1 dependents 718 downloads

Last updated 19 days agofrom:7a054c2207

Exports:adjacencyas.editmatrixas.editsetas.lp.mipas.mipbacktrackerblockIndexblockscheckDatamodelchoicepointconditioncontainsdatamodeldisjunctecheloneditarrayeditfileeditmatrixeditnameseditseteditTypeeliminateerrorLocalizererrorLocalizer_mipgenerateEditsgetAgetAbgetbgethgetHgetOpsgetVarsimpliedValuesis.editarrayis.editmatrixis.editsetisFeasibleisNormalizedisObviouslyInfeasibleisObviouslyRedundantisSubsetlocalizeErrorsneditsnormalizereduceseparatesubstValueviolatedEdits

Dependencies:clicpp11glueigraphlatticelifecyclelpSolveAPImagrittrMatrixpkgconfigrlangvctrs