Package: DCC 1.2.1

Kunxiang Ma

DCC: Data Cleaning Center for Survey and Assessment Data

Rule-driven, auditable cleaning of survey and assessment response data, implementing the WeianData Detect-Execute-Report workflow. Provides a multi-format, multi-encoding input layer (CSV, 'Excel', 'SPSS', 'Stata', 'SAS', Parquet, JSON), the dcc_data container with a provenance chain, level-0 structural diagnostics, five built-in response-quality detectors (missing items, straight-lining, response time, trap items, score anomalies), a declarative YAML rule engine, an execution engine with a cell-level audit log, answer-key scoring, multi-form to master item bank mapping, a normalized report model rendered as bilingual staff workbooks and HTML, complete statistical bundles, and versioned machine JSON/JSONL with findings-to-changes reconciliation, cell-level lineage tracing, and manifest-based one-command reproduction. Includes a protected bilingual strict project workbook and matching JSON contract with cell-addressed validation, non-mutating preflight, preview-first execution, and localized staff guidance. All formally supported input backends install with the package; PDF is optional rather than a fixed report output.

Authors:Kunxiang Ma [aut, cre], WEIAN DATA TECH Co., Ltd. [cph, fnd]

DCC_1.2.1.tar.gz
DCC_1.2.1.zip(r-4.7-any)DCC_1.2.1.zip(r-4.6-any)DCC_1.2.1.zip(r-4.5-any)
DCC_1.2.1.tgz(r-4.6-any)DCC_1.2.1.tgz(r-4.5-any)
DCC_1.2.1.tar.gz(r-4.7-any)DCC_1.2.1.tar.gz(r-4.6-any)
DCC_1.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DCC/json (API)

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

Bug tracker:https://github.com/weiandata/dcc/issues

On CRAN:

Conda:

4.70 score 60 exports 42 dependencies

Last updated from:26c7b66867. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK263
source / vignettesOK252
linux-releaseOK273
macos-releaseOK143
macos-oldrelOK161
windows-develOK195
windows-releaseOK185
windows-oldrelOK184
wasm-releaseOK145

Exports:dcc_apply_codebookdcc_audit_logdcc_capabilitiesdcc_checkdcc_cleaneddcc_codebook_changesdcc_configdcc_datadcc_detectdcc_detect_chunkeddcc_detect_encodingdcc_dictionarydcc_dispositionsdcc_doctordcc_executedcc_export_logdcc_findingsdcc_helpdcc_importdcc_item_mapdcc_l0_diagnosedcc_manifestdcc_map_formsdcc_mapping_findingsdcc_missing_statesdcc_provenancedcc_readdcc_read_configdcc_read_plandcc_read_reportdcc_reconciledcc_reportdcc_report_machinedcc_report_modeldcc_report_staffdcc_report_statisticaldcc_rerundcc_result_summarydcc_rulesdcc_rundcc_run_filesdcc_schemadcc_scoredcc_templatedcc_tracedcc_unhandleddcc_validate_configdcc_validate_datadcc_validate_jsondcc_validate_jsonldcc_validate_plandcc_validate_report_modeldcc_validate_rulesdcc_validation_errorsdcc_write_config_templatedetect_missing_itemsdetect_response_timedetect_score_anomalydetect_straightliningdetect_trap_items

Dependencies:arrowassertthatbitbit64cellrangerclicliprcpp11crayondata.tableforcatsgluehavenhmsjsonlitelifecyclemagrittrmintyopenxlsx2pillarpkgconfigprettyunitsprogresspurrrR6RcppreadODSreadrreadxlrematchrlangstringitibbletidyselecttzdbutf8vctrsvroomwithrwritexlyamlzip

Reproducible statistical reports with DCC
Rendered fromstatistical-report.Rmdusingknitr::rmarkdown

Last update: 2026-07-29
Started: 2026-07-15

The DCC cleaning pipeline: Detect, Execute, Report
A small dataset and a rule set | Detect | Execute | Report | Trace and reproduce | Larger-than-memory input
Rendered fromdcc-pipeline.Rmdusingknitr::rmarkdown

Last update: 2026-07-12
Started: 2026-07-12

Readme and manuals

Help Manual

Help pageTopics
Apply a declarative codebook to a datasetdcc_apply_codebook
Accessors for dcc_result objectsdcc_audit_log dcc_cleaned
Machine-readable DCC capability documentdcc_capabilities
Check a strict DCC project without changing datadcc_check
The planned changes of a codebook previewdcc_codebook_changes
A cleaning configurationdcc_config
The dcc_data containerdcc_data
Run a rule set against data (Detect stage)dcc_detect
Run record-local checks over a file in chunksdcc_detect_chunked
Detect the character encoding of a text filedcc_detect_encoding
Canonical variable dictionarydcc_dictionary
Terminal dispositions of a cleaning resultdcc_dispositions
Run every validator over a dataset and rule setdcc_doctor
Execute actions on detected findings (Execute stage)dcc_execute
Export an audit log for external auditorsdcc_export_log
The dcc_findings tabledcc_findings
Explain a DCC workflow code in Chinese or Englishdcc_help
Strict canonical importdcc_import
Master item map of a form-mapped datasetdcc_item_map
Level-0 structural diagnosticsdcc_l0_diagnose
Build a reproducibility manifest for a cleaning rundcc_manifest
Map multi-form responses onto the master item bankdcc_map_forms
Mapping problems found while aligning formsdcc_mapping_findings
Canonical cell-level missing statesdcc_missing_states
Provenance chain of a dcc_data objectdcc_provenance
Read a data file into a dcc_data objectdcc_read
Read an Excel cleaning-plan configurationdcc_read_config
Read a strict DCC Excel or JSON plandcc_read_plan
Read report of a dcc_data objectdcc_read_report
Reconcile findings against logged changes (closed loop)dcc_reconcile
Generate a cleaning report (Report stage)dcc_report
Render the machine report bundledcc_report_machine
Build and validate the normalized report modeldcc_report_model dcc_validate_report_model
Render the bilingual staff reportdcc_report_staff
Render the statistical report bundledcc_report_statistical
Re-run a cleaning pipeline from its manifest and verify the outputdcc_rerun
Create a structured AI summary of a DCC resultdcc_result_summary
Load a declarative rule set from a YAML filedcc_rules
Run a cleaning workflow with one commanddcc_run
Output files written by a rundcc_run_files
Published JSON Schema for a DCC objectdcc_schema
Score responses against an answer keydcc_score
Create the strict bilingual DCC Excel templatedcc_template
Trace the cleaning history of a record or celldcc_trace
Findings left unhandled by executiondcc_unhandled
Validate a cleaning configurationdcc_validate_config
Validate data against a rule set before detectiondcc_validate_data
Validate DCC JSON and JSON Lines artifactsdcc_validate_json dcc_validate_jsonl
Validate a strict DCC project plandcc_validate_plan
Validate a rule set before it is useddcc_validate_rules
The failing issues of a validation reportdcc_validation_errors
Write a starter Excel cleaning-plan templatedcc_write_config_template
Detect excessive item nonresponse per respondentdetect_missing_items
Detect implausibly fast or anomalous response timesdetect_response_time
Detect group-wise score anomaliesdetect_score_anomaly
Detect straight-lining (longstring)detect_straightlining
Detect failed trap (attention-check) itemsdetect_trap_items