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editrules (version 2.9.5)

Parsing, Applying, and Manipulating Data Cleaning Rules

Description

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.

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Install

install.packages('editrules')

Monthly Downloads

512

Version

2.9.5

License

GPL-3

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Repository

https://github.com/data-cleaning/editrules

Maintainer

Edwin Jonge

Last Published

May 4th, 2024

Functions in editrules (2.9.5)

Create an editmatrix with categorical variables

Bring an (edit) matrix to reduced row echelon form.

duplicated.editmatrix

Check for duplicate edit rules

Check data against a datamodel

Example editrules, used in vignette

editrules_package

An overview of the function of package editrules

Eliminate a variable from a set of edit rules

Read general edits

Decouple a set of conditional edits

duplicated.editarray

Check for duplicate edit rules

editrules.plotting

Graphical representation of edits

Determine edittypes in editset based on 'contains(E)'

Parse textual, categorical edit rules to an editarray

Returns the coefficient matrix A of linear (in)equalities

Returns augmented matrix representation of edit set.

The errorLocation object

Expand an edit expression

Read edits edits from free-form textfile

Returns the operator part of a linear (in)equality editmatrix E

Create an editmatrix

retrieve edit names from editarray

Get upperbounds of edits, given the boundaries of all variables

get seprator used to seperate variables from levels in editarray

Get named logical array from editarray

getVars.editarray

get variable names in editarray

get index list from editmatrix

Derive all essentially new implicit edits

get names of variables in a set of edits

getVars.cateditmatrix

Returns the variable names of an (in)equality editmatrix E

retrieve level names from editarray

Field code forest algorithm

editarray: logical array where every column corresponds to one level of one variable. Every row is an edit. Every edit denotes a *forbidden* combination.

Create a backtracker object for error localization

getVars.editlist

get variable names

getVars.editmatrix

Returns the variable names of an (in)equality editmatrix E

errorLocalizer_mip

Localize errors using a MIP approach.

Compute index from array part of editarray

Check object class

Check which edits are dominated by other ones.

Check if an editmatrix is normalized

Parse a character vector of edits

Returns the derivation history of an edit matrix or array

Localize errors on records in a data.frame.

Check consistency of set of edits

Number of edits Count the number of edits in a collection of edits.

Returns the constant part b of a linear (in)equality

Retrieve values stricktly implied by rules

Normalizes an editmatrix

Derive textual representation from (partial) indices

newerrorlocation

Generate new errorlocation object

Parse a mixed edit

Parse a categorical edit expression

softEdits.cateditmatrix

Derive editmatrix with soft constraints. This is a utility function that is used for constructing a mip/lp problem.

print.editarray

print editarray

Parse a numerical edit expression

print.cateditmatrix

print cateditmatrix

Workhorse function for localizeErrors

isObviouslyInfeasible

Check for obvious contradictions in a set of edits

isObviouslyRedundant

Find obvious redundancies in set of edits

softEdits.editarray

Derive editmatrix with soft constraints based on boundaries of variables. This is a utility function that is used for constructing a mip/lp problem.

print.backtracker

print a backtracker

print.editmatrix

print editmatrix

Create an editmatrix object from its constituing attributes.

print.editsummary

Simplify logical mixed edits in an editset

Replace a variable by a value in a set of edits.

print.errorLocation

Print object of class errorLocation

parse categorial edit

removeRedundantDummies

Remove redundant dummy variables

print.locationsummary

Check data against constraints

Remove redundant variables and edits.

print.violatedEdits

Print violatedEdits

softEdits.editmatrix

Derive editmatrix with soft constraints based on boundaries of variables. This is a utility function that is used for constructing a mip/lp problem.

Row index operator for editmatrix

Derive editmatrix with soft constraints based on boundaries of variables. This is a utility function that is used for constructing a mip/lp problem.

Separate an editset into its disconnected blocks and simplify

Rewrite an editset and reported values into the components needed for a mip solver

Decompose a matrix or edits into independent blocks

Backtracker: a flexible and generic binary search program

Transform a found solution into a categorical record

Coerce x to an editset

Write an editset into a mip representation

Derive adjecency matrix from collection of edits

Coerce a matrix to an edit matrix.

Coerces a mip object into an lpsolve object

as.character.cateditmatrix

Coerce an cateditmatrix to a character vector

Add dummy variable to the data.frames, these are needed for errorlocations etc.

Summarize data model of an editarray in a data.frame

Determine which edits contain which variable(s)

contains.boolmat

Determine if a boolean matrix contains var

Get condition matrix from an editset.