Аудит качества табличных данных

★ 6.6 · data

dataset-quality-audit is a Claude Code skill that runs a 12-dimension quality audit on tabular data in CSV, Excel, TSV, and JSON formats. It checks for missing values, duplicate rows, outliers via the IQR method, type inconsistencies, format issues in dates and phone numbers, whitespace anomalies, constant columns, distribution skewness, cardinality anomalies, and cross-column logical consistency. Each dimension receives a score from 0 to 100, and the file gets an overall grade from F to A+ along with actionable fix suggestions. The skill is invoked via a Python script (Python 3.8+, pandas, numpy) with options to specify ID columns for uniqueness checks, date columns, file encoding, and row sampling for large files — output is a structured JSON report. It's built for data analysts and data engineers who need to assess dataset readiness before model training or ingestion into a data warehouse.