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Trade Observations Data Quality Suite — Audit, Normalisation & Missing-Value Fill
x402
Trade Observations Data Quality Suite — Audit, Normalisation & Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs three local analytical reports on trade observation records: record quality audit, string normalisation, and explicit missing-value fill for export_amount and import_amount fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Trade observations — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied trade observations records (export_amount, import_amount). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports covering: (1) a record quality audit flagging issues such as nulls, format violations, or anomalies across the supplied rows; (2) string normalisation results for the region and date fields; and (3) an explicit missing-value fill for the specified field (export_amount or import_amount) using the chosen method (zero, mean, or median). Results are scoped to the supplied data only — no external lookups or predictions are made.
Example use cases
Pre-analysis trade data cleanup
“I have a batch of 120 trade observation records with region names that need normalising and some null export_amount values — can you run the quality audit, string normalisation, and fill those missing export amounts using the mean method?”
Import data completeness check
“Can you audit these 80 trade rows for record quality issues and fill any missing import_amount values using median imputation? The rows include region, date, export_amount, and import_amount.”
Regional trade string standardisation
“My trade dataset has inconsistent region labels and a few blank import_amount cells across 35 rows — please run all three reports: quality audit, string normalisation, and zero-fill for the missing import amounts.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-06-208?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 trade observation rows (with export_amount and import_amount columns) and need all three data quality operations — audit, string normalisation, and missing-value imputation — bundled in a single low-cost call. It is ideal for pre-processing pipelines where no external data lookup, live prediction, or professional assessment is required, and all computation is done locally on the supplied data.
Side effects
- Rows array exceeds 200 items — request rejected with validation error
- Invalid date format (not YYYY-MM-DD) causes row-level audit failure
- row_id missing or empty — schema validation error
- export_amount or import_amount outside ±1,000,000,000,000 range — rejected
- Invalid method enum value (not zero/mean/median) — schema error
- Invalid field enum value (not export_amount/import_amount) — schema error
- Payment of 0.01 USDC not received — request blocked by x402 paywall
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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