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dataMaid (version 1.4.2)

A Suite of Checks for Identification of Potential Errors in a Data Frame as Part of the Data Screening Process

Description

Data screening is an important first step of any statistical analysis. dataMaid auto generates a customizable data report with a thorough summary of the checks and the results that a human can use to identify possible errors. It provides an extendable suite of test for common potential errors in a dataset.

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Install

install.packages('dataMaid')

Monthly Downloads

905

Version

1.4.2

License

GPL-2

Issues

Pull Requests

Stars

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Repository

https://github.com/ekstroem/dataMaid

Homepage

https://doi.org/10.18637/jss.v090.i06

Maintainer

Claus Ekstrom

Last Published

April 13th, 2025

Functions in dataMaid (1.4.2)

Summary function for missing values

defaultIntegerChecks

Default checks for integer variables

defaultIntegerSummaries

Default summary functions for integer variables

defaultHavenlabelledChecks

Default checks for haven_labelled variables

defaultHavenlabelledSummaries

Default summary functions for haven_labelled variables

A checkFunction

Create object of class checkResult

identifyMissing

A checkFunction for identifying miscoded missing values.

defaultLogicalChecks

Default checks for logical variables

defaultLogicalSummaries

Default summary functions for logical variables

Create an object of class checkFunction

Example data with zero-inflated variables

Extract the contents of the attribute description

identifyWhitespace

A checkFunction for identifying whitespace

defaultLabelledSummaries

Default summary functions for labelled variables

Check if a variable consists of Danish CPR numbers

defaultLabelledChecks

Default checks for labelled variables

identifyOutliersTBStyle

A checkFunction for identifying outliers Turkey Boxstole style

defaultCharacterChecks

Default checks for character variables

defaultCharacterSummaries

Default summary functions for character variables

Check if a variable has a class supported by dataMaid

summaryFunction for minimum and maximum

identifyOutliers

A checkFunction for identifying outliers

defaultDateChecks

Default checks for Date variables

Semi-artificial data about the US presidents

summaryFunction for quartiles

summaryFunction that finds reference level for factor variables

Produce a data codebook

Extended example data to test the features of dataMaid

Produce tables for the makeDataReport visualizations.

Set visual arguments for makeDataReport

Check if a variable only contains a single value

Set summary arguments for makeDataReport

Check if a variable qualifies as a key

Summary function for original class

Create an object of class visualFunction

whoami_available

Find out if the whoami package binaries is installed (git + whoami)

Produce distribution plots

Produce distribution plots using ggplot from ggplot2.

Summarize a variable/dataset

Simplified Rmarkdown rendering

Set check arguments for makeDataReport

identifyCaseIssues

A checkFunction for identifying case issues

A checkFunction for identifying sparsely represented values (loners)

defaultDateSummaries

Default summary functions for Date variables

defaultNumericChecks

Default checks for numeric variables

defaultNumericSummaries

Default summary functions for numeric variables

summaryFunction

Create an object of class summaryFunction

Produce a data report

Create object of class summaryResult

messageGenerator

Produce a message for the output of a checkFunction

Small example data to show the features of dataMaid

summaryFunction for unique values

summaryFunction for central values

Semi-artificial data about masterpieces of art

allSummaryFunctions

Overview of all available summaryFunctions

allCheckFunctions

Overview of all available checkFunctions

Vector of all variable classes in dataMaid

Produce distribution plots in the base R (graphics) style using plot and barplot

allVisualFunctions

Overview of all available visualFunctions

basicVisualCFLB

importFrom stats na.omit

defaultFactorChecks

Default checks for factor variables

Extract the contents of the attribute classes

defaultFactorSummaries

Default summary functions for factor variables

bigPresidentData

Semi-artificial data about the US presidents (extended version)

Perform checks of potential errors in variable/dataset