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


[Up] [Top]

Documentation for package ‘dataMaid’ version 1.4.1

Help Pages

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