DataQuality Assess
Assess the quality of a tabular dataset (CSV file or JSON array of records). Returns per-column statistics (data type, missing count/percentage, unique values, numeric min/max/mean/std, categorical mode/top values), overall summary (total rows, columns, complete cases), and warnings for columns with >20% missing values, zero variance, potential outliers (>3 SD from mean), and highly correlated numeric pairs (|r| > 0.95). Pure local computation with pandas -- no external API calls. Useful for pr…
Overview
Assess the quality of a tabular dataset (CSV file or JSON array of records). Returns per-column statistics (data type, missing count/percentage, unique values, numeric min/max/mean/std, categorical mode/top values), overall summary (total rows, columns, complete cases), and warnings for columns with >20% missing values, zero variance, potential outliers (>3 SD from mean), and highly correlated numeric pairs (|r| > 0.95). Pure local computation with pandas -- no external API calls. Useful for pre-analysis data validation and quality control.
Schema
JSON Schema the agent (or your API call) must match.
Examples (1)
Default DataQuality Assess call
Anonymous-safe example. Rate-limited; no sign-in required.
Identifiers
- Catalog ID
- tu_DataQuality_assess
- Tool name
- DataQuality_assess
- Added
- 2026-05-01 00:58Z
- Tags
- tooluniverse