Package: DataAudit 0.1.0

DataAudit: Comprehensive Data Quality Auditing and Validation

Provides tools for systematic assessment, validation, and reporting of data quality. The package detects common data-quality problems including missing or blank values, duplicate observations, infinite values, constant and near-zero variance variables, outliers, invalid ranges and categories, type and pattern violations, problematic dates and identifiers, sequence errors, dependency violations, and cross-variable inconsistencies. It also supports reusable validation rules, integrated audit reports, and standardized data-quality scoring for reproducible data-quality assessment workflows.

Authors:Vinodh Kumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]

DataAudit_0.1.0.tar.gz
DataAudit_0.1.0.zip(r-4.7-any)DataAudit_0.1.0.zip(r-4.6-any)DataAudit_0.1.0.zip(r-4.5-any)
DataAudit_0.1.0.tgz(r-4.6-any)DataAudit_0.1.0.tgz(r-4.5-any)
DataAudit_0.1.0.tar.gz(r-4.7-any)DataAudit_0.1.0.tar.gz(r-4.6-any)
DataAudit_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DataAudit/json (API)

# Install 'DataAudit' in R:

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

Bug tracker:https://github.com/vinodhpmd/dataaudit/issues

On CRAN:

4.18 score 3 stars 186 downloads 26 exports 0 dependencies

Last updated from:c0639caf2e. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	131
source / vignettes	OK	165
linux-release	OK	130
macos-release	OK	180
macos-oldrel	OK	163
windows-devel	OK	94
windows-release	OK	93
windows-oldrel	OK	82
wasm-release	OK	96

Exports:apply_audit_rules audit_data audit_rules audit_score blank_check case_check category_check consistency_check constant_check data_overview date_check dependency_check duplicate_check group_sequence_check id_check infinite_check length_check missing_check nzv_check outlier_check pattern_check range_check sequence_check type_check unique_check whitespace_check

Dependencies:

Getting Started with DataAudit

Rendered fromgetting-started-with-dataaudit.Rmdusingknitr::rmarkdown

Last update: 2026-07-28
Started: 2026-07-28

Help page	Topics
Apply Data Audit Rules	apply_audit_rules
Perform a General Data Quality Audit	audit_data
Create Data Audit Rules	audit_rules
Calculate a Data Quality Score	audit_score
Check Blank Values	blank_check
Check Case Consistency	case_check
Check Categorical Values	category_check
Check Consistency Between Two Variables	consistency_check
Check Constant Variables	constant_check
Data Overview	data_overview
Check Date Values	date_check
Check Conditional Variable Dependency	dependency_check
Check Duplicate Rows	duplicate_check
Check Sequence Integrity Within Groups	group_sequence_check
Check Identifier Integrity	id_check
Check Infinite Values	infinite_check
Check Character Length	length_check
Check Missing Values	missing_check
Check Near-Zero Variance Variables	nzv_check
Check Numeric Outliers	outlier_check
Check Character Patterns	pattern_check
Print a DataAudit Report	print.DataAuditReport
Print a DataAudit Rule Result	print.DataAuditRuleResult
Print a DataAudit Score	print.DataAuditScore
Check Values Against a Valid Range	range_check
Check Numeric Sequence Integrity	sequence_check
Summarize a DataAudit Report	summary.DataAuditReport
Summarize a DataAudit Rule Result	summary.DataAuditRuleResult
Check Variable Types	type_check
Check Unique Identifier	unique_check
Check Leading and Trailing Whitespace	whitespace_check

Package: DataAudit 0.1.0

DataAudit: Comprehensive Data Quality Auditing and Validation

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Help Manual

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