dataset-quality-audit

# dataset-quality-audit A data quality auditing tool that runs 12-dimension quality checks on tabular data, producing per-dimension scores (0–100), an overall grade, and actionable fix suggestions. ## Capabilities | Dimension | Description | |-----------|-------------| | Missing Values | Count and percentage of null/NaN values per column | | Duplicate Rows | Number and percentage of fully duplicated rows | | Type Consistency | Mixed types within a single column (e.g., numbers mixed with text) | | Value Range / Outliers | Outlier detection using the IQR method | | Format Compliance | Consistency of date, email, phone number, and other formatted fields | | Uniqueness Constraints | Whether ID-type columns contain duplicates | | Whitespace Issues | Leading/trailing spaces, empty strings, whitespace-only values | | Constant Columns | Columns with only a single unique value (zero information) | | Distribution Skewness | Whether numeric columns have excessive skewness | | Column Naming | Spaces, special characters, or inconsistent casing in column names | | Cardinality Anomalies | Unusually high or low number of unique values | | Cross-Column Consistency | Logical checks across columns (e.g., start date before end date) | ## Quick Start ```bash # Basic quality check python3 scripts/data_quality_checker.py data.csv # Save report as JSON python3 scripts/data_quality_checker.py data.csv --output report.json # Specify ID columns (for uniqueness checks) python3 scripts/data_qualit...