Package: data.checker 2.0.0

Analysis Standards and Pipelines Team (ONS)

data.checker: Data Checker for Validating Data Frames Against Defined Schema

Validates data frames against a defined schema. Produces a report of the checks performed and any issues found, with index and entry value where appropriate. Backend checks are performed using pointblank Richard Iannone et al (2025) <doi:10.32614/CRAN.package.pointblank>.

Authors:Crown Copyright [cph], Analysis Standards and Pipelines Team [cre, aut]

data.checker_2.0.0.tar.gz
data.checker_2.0.0.zip(r-4.7-any)data.checker_2.0.0.zip(r-4.6-any)data.checker_2.0.0.zip(r-4.5-any)
data.checker_2.0.0.tgz(r-4.6-any)data.checker_2.0.0.tgz(r-4.5-any)
data.checker_2.0.0.tar.gz(r-4.7-any)data.checker_2.0.0.tar.gz(r-4.6-any)
data.checker_2.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
data.checker/json (API)

# Install 'data.checker' in R:
install.packages('data.checker', repos = c('https://onsdigital.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/onsdigital/data.checker/issues

Pkgdown/docs site:https://onsdigital.github.io

On CRAN:

Conda:

6.35 score 5 stars 3 scripts 304 downloads 24 exports 91 dependencies

Last updated from:80f698f323. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK184
source / vignettesOK195
linux-releaseOK132
macos-releaseOK191
macos-oldrelOK210
windows-develOK87
windows-releaseOK92
windows-oldrelOK89
wasm-releaseOK135

Exports:%>%add_checkadd_check_customadd_qa_entrycheckcheck_and_exportcheck_backseriescheck_colnamescheck_column_contentscheck_completenesscheck_duplicatescheck_schema_contents_against_dfcheck_typesexporthard_checks_statusiqr_boundsis_valid_column_valuesis_valid_schemalog_htmllog_to_tablenew_validatortypes_to_classesvalidate_and_convert_date_formatsz_score

Dependencies:askpassbase64encbigDbitopsblastulablobbriobslibcachemcallrclicommonmarkcpp11crayoncurlDBIdbplyrdescdiffobjdigestdplyrevaluatefarverfastmapfontawesomefsgenericsgetPassgluegtherehighrhmshtmltoolshtmlwidgetshttrjquerylibjsonlitejuicyjuiceknitrlabelinglifecyclelitedownlubridatemagrittrmarkdownmemoisemimeopensslotelpillarpkgbuildpkgconfigpkgloadpointblankpraiseprocessxpspurrrR6rappdirsRColorBrewerRcppreactablereactRrlangrmarkdownrprojrootrstudioapisassscalesstringistringrsystestthattibbletidyrtidyselecttimechangetinytextomleditutf8uuidV8vctrsviridisLitewaldowithrxfunxml2yaml

Data checker
The basics | Example dataset: | Example schema: | Initialising the data checker | Running checks | Exporting your log | Optional function arguments | Setting up the schema | Mandatory fields | Optional checks: | Loading from file | Custom checks | Custom log entries
Rendered fromgetting_started.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2026-01-08

Export formats
Exporting results | html | csv | json | yaml
Rendered fromexport_formats.Rmdusingknitr::rmarkdown

Last update: 2026-01-08
Started: 2026-01-08

Readme and manuals

Help Manual

Help pageTopics
Add a custom check to the validatoradd_check
Add a custom check to the validatoradd_check_custom
Add a QA Entry to the validator's QA Logadd_qa_entry
Validate a Validator Objectcheck
Validate data against a schema and output resultscheck_and_export
Check backseries consistencycheck_backseries
Check Column Names against schemacheck_colnames
Check Column Contents against schema and checkscheck_column_contents
Check dataset for missing columnscheck_completeness
Check for duplicate rows. Can use subset of columns to check for duplicates if 'duplicates_cols' is specified in the schema. Otherwise, all columns are used for duplicate check.check_duplicates
Check schema contents against the data frame providedcheck_schema_contents_against_df
Check Column Types and Classescheck_types
Generic export functionexport
Export Validator Logexport.Validator
Check the status of errors and warnings in the validator loghard_checks_status
Flag outliers based on Interquartile Range (IQR). Outliers are flagged if they are below Q1 - (mulitplier * IQR) or above Q3 + (multiplier * IQR).iqr_bounds
Check column contents validis_column_contents_valid
Check type of column in schema is validis_type_valid
Check that max values are not less than min values in column schemais_valid_column_values
Check if the schema is validis_valid_schema
Generate HTML Representation of a Loglog_html
Log pointblank validation outcomes to a validator loglog_pointblank_outcomes
Convert Validator Log to Tablelog_to_table
Validator Constructornew_validator
Print Validator Logprint.Validator
Run column checksrun_checks
Convert complex types to the correct types and classestypes_to_classes
Validate date formats in the schema This function checks that any date formats specified in the schema are valid and can be parsed correctly.validate_and_convert_date_formats
Check Z Score of Numeric Columnsz_score