Package: dataMaid 1.4.0

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

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.

Authors:Anne Helby Petersen [aut], Claus Thorn Ekstrøm [aut, cre]

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dataMaid.pdf |dataMaid.html✨
dataMaid/json (API)

# Install 'dataMaid' in R:

install.packages('dataMaid', repos = c('https://ekstroem.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ekstroem/datamaid/issues

Datasets:

artData - Semi-artificial data about masterpieces of art
bigPresidentData - Semi-artificial data about the US presidents
exampleData - Example data with zero-inflated variables
presidentData - Semi-artificial data about the US presidents
testData - Extended example data to test the features of dataMaid
toyData - Small example data to show the features of dataMaid

On CRAN:

data-cleaning data-screening reproducible-research

7.48 score 143 stars 209 scripts 1.0k downloads 1 mentions 62 exports 75 dependencies

Last updated 3 years agofrom:d7571007db. Checks:OK: 1 ERROR: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 02 2024
R-4.5-win	ERROR	Nov 02 2024
R-4.5-linux	ERROR	Nov 02 2024
R-4.4-win	ERROR	Nov 02 2024
R-4.4-mac	ERROR	Nov 02 2024
R-4.3-win	ERROR	Nov 02 2024
R-4.3-mac	ERROR	Nov 02 2024

Exports:allCheckFunctions allClasses allSummaryFunctions allVisualFunctions basicVisual centralValue check checkFunction checkResult classes classes<-countMissing defaultCharacterChecks defaultCharacterSummaries defaultDateChecks defaultDateSummaries defaultFactorChecks defaultFactorSummaries defaultHavenlabelledChecks defaultHavenlabelledSummaries defaultIntegerChecks defaultIntegerSummaries defaultLabelledChecks defaultLabelledSummaries defaultLogicalChecks defaultLogicalSummaries defaultNumericChecks defaultNumericSummaries description description<-identifyCaseIssues identifyLoners identifyMissing identifyNums identifyOutliers identifyOutliersTBStyle identifyWhitespace isCPR isEmpty isKey isSingular isSupported makeCodebook makeDataReport messageGenerator minMax quartiles refCat render setChecks setSummaries setVisuals standardVisual summarize summaryFunction summaryResult tableVisual uniqueValues variableType visualFunction visualize whoami_available

Dependencies:askpass base64enc bit bit64 bslib cachem cli clipr colorspace cpp11 crayon curl DEoptimR digest evaluate fansi farver fastmap fontawesome forcats fs ggplot2 glue gridExtra gtable haven highr hms htmltools httr isoband jquerylib jsonlite knitr labeling lattice lifecycle magrittr MASS Matrix memoise mgcv mime munsell nlme openssl pander pillar pkgconfig prettyunits progress R6 rappdirs RColorBrewer Rcpp readr rlang rmarkdown robustbase sass scales stringi sys tibble tidyselect tinytex tzdb utf8 vctrs viridisLite vroom whoami withr xfun yaml

Extending dataMaid

Anne Helby Petersen and Claus Thorn Ekstrøm

Rendered fromextending_dataMaid.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2020-07-03
Started: 2017-10-13

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Overview of all available checkFunctions	allCheckFunctions
Vector of all variable classes in 'dataMaid'	allClasses
Overview of all available summaryFunctions	allSummaryFunctions
Overview of all available visualFunctions	allVisualFunctions
Semi-artificial data about masterpieces of art	artData
Produce distribution plots in the base R (graphics) style using 'plot' and 'barplot'	basicVisual
importFrom stats na.omit	basicVisualCFLB
Semi-artificial data about the US presidents (extended version)	bigPresidentData
summaryFunction for central values	centralValue
Perform checks of potential errors in variable/dataset	check
Create an object of class checkFunction	checkFunction
Create object of class checkResult	checkResult
Extract the contents of the attribute 'classes'	classes classes<-
Summary function for missing values	countMissing
Default checks for character variables	defaultCharacterChecks
Default summary functions for character variables	defaultCharacterSummaries
Default checks for Date variables	defaultDateChecks
Default summary functions for Date variables	defaultDateSummaries
Default checks for factor variables	defaultFactorChecks
Default summary functions for factor variables	defaultFactorSummaries
Default checks for haven_labelled variables	defaultHavenlabelledChecks
Default summary functions for haven_labelled variables	defaultHavenlabelledSummaries
Default checks for integer variables	defaultIntegerChecks
Default summary functions for integer variables	defaultIntegerSummaries
Default checks for labelled variables	defaultLabelledChecks
Default summary functions for labelled variables	defaultLabelledSummaries
Default checks for logical variables	defaultLogicalChecks
Default summary functions for logical variables	defaultLogicalSummaries
Default checks for numeric variables	defaultNumericChecks
Default summary functions for numeric variables	defaultNumericSummaries
Extract the contents of the attribute 'description'	description description<-
Example data with zero-inflated variables	exampleData
A checkFunction for identifying case issues	identifyCaseIssues
A checkFunction for identifying sparsely represented values (loners)	identifyLoners
A checkFunction for identifying miscoded missing values.	identifyMissing
A checkFunction	identifyNums
A checkFunction for identifying outliers	identifyOutliers
A checkFunction for identifying outliers Turkey Boxstole style	identifyOutliersTBStyle
A checkFunction for identifying whitespace	identifyWhitespace
Check if a variable consists of Danish CPR numbers	isCPR
Check if a variable qualifies as a key	isKey
Check if a variable only contains a single value	isEmpty isSingular
Check if a variable has a class supported by dataMaid	isSupported
Produce a data codebook	makeCodebook
Produce a data report	makeDataReport
Produce a message for the output of a checkFunction	messageGenerator
summaryFunction for minimum and maximum	minMax
Semi-artificial data about the US presidents	presidentData
summaryFunction for quartiles	quartiles
summaryFunction that finds reference level for factor variables	refCat
Simplified Rmarkdown rendering	render
Set check arguments for makeDataReport	setChecks
Set summary arguments for makeDataReport	setSummaries
Set visual arguments for makeDataReport	setVisuals
Produce distribution plots using ggplot from ggplot2.	standardVisual
Summarize a variable/dataset	summarize
Create an object of class summaryFunction	summaryFunction
Create object of class summaryResult	summaryResult
Produce tables for the makeDataReport visualizations.	tableVisual
Extended example data to test the features of dataMaid	testData
Small example data to show the features of dataMaid	toyData
summaryFunction for unique values	uniqueValues
Summary function for original class	variableType
Create an object of class visualFunction	visualFunction
Produce distribution plots	visualize
Find out if the whoami package binaries is installed (git + whoami)	whoami_available