Individual skill
portaljs-check-data-quality
Audit a local or remote tabular file (CSV/TSV) for common data quality issues — schema, nulls, types, duplicates. Read-only. Use when a dataset needs a quality check before publishing, or a showcase renders wrong (blank cells, garbled numbers, an unsortable date column) and the cause needs isolating.
skills/portaljs-check-data-quality/SKILL.md
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- Last checked
- Nov 3, 2026
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- 2,370
- Repository last updated
- Oct 28, 2026
- License
- MIT
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- data-portal Repository topic
- ckan Repository topic
- nextjs Repository topic
- open-data-portal Repository topic
- data-mesh Repository topic
- datahub Repository topic
- open-data Repository topic
- openmetadata Repository topic
- dataverse Repository topic
- dkan Repository topic
- portaljs Declared skill tag
- data-portal Declared skill tag
- data-quality Declared skill tag
- audit Declared skill tag
- csv Declared skill tag
- validation Declared skill tag
- security Derived category
- data Derived category
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# PortalJS — Check Data Quality
## Overview
Run a read-only quality audit of one CSV or TSV file, local or remote, and return a
structured JSON report. The audit profiles every column — null/blank counts, inferred
value types, numeric ranges, likely year/date fields — and flags duplicate rows,
duplicate values in identifier-like columns, ambiguous overlapping year columns (e.g.
`calendar year` vs `fiscal year`), and mixed-type columns. It never edits the source
file, `datasets.json`, or any other project file; it only reads the target file (a
remote URL is downloaded to a temp file that is deleted before the run ends) and
prints a report. Use it before publishing a dataset with `portaljs-add-dataset`, or to
diagnose why a showcase renders wrong.
