validate: Data Validation Infrastructure

Declare data validation rules and data quality indicators; confront data with them and analyze or visualize the results. The package supports rules that are per-field, in-record, cross-record or cross-dataset. Rules can be automatically analyzed for rule type and connectivity. See also Van der Loo and De Jonge (2018) <doi:10.1002/9781118897126>, chapter 6.

Version: 0.9.3
Depends: R (≥ 3.1.3), methods
Imports: stats, graphics, settings, yaml
Suggests: tinytest (≥ 0.9.6), knitr, rmarkdown
Enhances: lumberjack
Published: 2019-12-16
Author: Mark van der Loo ORCID iD [cre, aut], Edwin de Jonge ORCID iD [aut], Paul Hsieh [ctb]
Maintainer: Mark van der Loo <mark.vanderloo at gmail.com>
BugReports: https://github.com/data-cleaning/validate/issues
License: GPL-3
URL: https://github.com/data-cleaning/validate
NeedsCompilation: yes
Citation: validate citation info
Materials: NEWS
In views: OfficialStatistics
CRAN checks: validate results

Downloads:

Reference manual: validate.pdf
Vignettes: 03_Indicators
01_Introduction
02_Rules_in_text_files
Data Validation Infrastructure for R
Package source: validate_0.9.3.tar.gz
Windows binaries: r-devel: validate_0.9.3.zip, r-release: validate_0.9.3.zip, r-oldrel: validate_0.9.3.zip
macOS binaries: r-release: validate_0.9.3.tgz, r-oldrel: validate_0.9.3.tgz
Old sources: validate archive

Reverse dependencies:

Reverse depends: errorlocate, validatetools
Reverse imports: dcmodify, deductive, iNZightTools, rspa

Linking:

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