c(person("Dania M.", "Rodriguez", email = "dmrodz@gmail.com", role = c("aut", "cre")),
person("P3S Corporation", role = "cph")
)
Dania M. Rodriguez [aut, cre],
P3S Corporation [cph]

person("Emmanuel-Lin", "Toulemonde", email = "el.toulemonde@protonmail.com", role = c("aut", "cre"))
Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of data.table efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.
R (>= 3.3.0), lubridate, stringr, Matrix

knitr, rmarkdown, kableExtra, pander, testthat

R (>= 3.3.0), lubridate, stringr, Matrix, progress

knitr, rmarkdown, kableExtra, pander, testthat (>= 2.0.0)

Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of 'data.table' efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.

Performs variable level data quality checks and generates
summary statistics
Madhav Kumar <madhavkumar2005@gmail.com> and Shreyes Upadhyay
<shreyes.upadhyay@gmail.com>
The package performs variable level data quality checks including
missing values, unique values, frequency tables, and generates summary
statistics

Reproducible Data Screening Checks and Report of Possible Errors
Data screening is an important first step of any statistical
analysis. 'dataReporter' 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. See Petersen AH, Ekstrøm CT (2019). "dataMaid: Your Assistant for Documenting Supervised Data Quality Screening in R." _Journal of Statistical Software_, *90*(6), 1-38 <doi:10.18637/jss.v090.i06> for more information.
'aggregateForBarplot.R' 'aggregateForHistogram.R'
'allCheckFunctions.R' 'allClasses.R' 'allSummaryFunctions.R'
'allVisualFunctions.R' 'allXFunctions.R' 'makeXFunction.R'
'visualFunction.R' 'basicVisual.R' 'summaryFunction.R'
'centralValue.R' 'check.R' 'checkResult.R' 'messageGenerator.R'
'checkFunction.R' 'identifyMissing.R' 'minMax.R' 'classes.R'
'countMissing.R' 'dataReporter-package.R'
'dataReporter_as_factor.R' 'description.R'
'identifyCaseIssues.R' 'identifyLoners.R' 'identifyNums.R'
'identifyOutliers.R' 'identifyOutliersTBStyle.R'
'identifyWhitespace.R' 'isCPR.R' 'isSingular.R' 'isEmpty.R'
'isKey.R' 'isSupported.R' 'makeCodebook.R' 'makeDataReport.R'
'misc.R' 'quartiles.R' 'refCat.R' 'render.R' 'setChecks.R'
'setSummaries.R' 'setVisuals.R' 'smartNum.R' 'standardVisual.R'
'summarize.R' 'summaryResult.R' 'tableVisual.R'
'uniqueValues.R' 'unpackLabelled.R' 'utility.R'
'variableType.R' 'visualize.R'