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Company Filing Inventories — Record Quality Audit, String Normalisation & Missing-Value Fill
x402
Company Filing Inventories — Record Quality Audit, String 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 2026-10-20).
Audits, normalises, and fills missing values in company filing inventory records (available_filings, expected_filings) across up to 200 rows, producing 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company filing inventories — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied company filing inventories records (available_filings, expected_filings). 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 reports covering: (1) a record quality audit flagging data issues across the supplied rows, (2) a string normalisation report standardising company group and other text fields, and (3) an explicit missing-value fill report showing imputed values for the chosen field (available_filings or expected_filings) using the selected method (zero, mean, or median). All reports are generated locally with no external lookups.
Example use cases
Pre-pipeline filing data quality check
“Before I load this batch of 120 company filing records into our database, can you audit the data quality, normalise the company group strings, and fill any null expected_filings values using the mean — the rows have dates, row IDs, and both available and expected filing counts?”
Missing available_filings imputation with zero-fill
“I've got 80 rows of filing inventory data for various company groups and some of the available_filings values are missing — can you fill those gaps using zero-fill and also run the string normalisation and record quality audit at the same time?”
Compliance dataset validation before reporting
“We need to validate our quarterly filing inventory records for compliance review — please run all three checks (quality audit, string normalisation, and missing-value fill using median) on these 200 rows of expected_filings and available_filings data grouped by company.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-17-208?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need batch data quality processing on company filing inventory records specifically — combining quality auditing, string normalisation, and missing-value imputation in a single low-cost call. It is best suited for pre-pipeline validation or compliance data preparation involving available_filings and expected_filings columns, where no live data lookup or external enrichment is needed and all processing is purely local and analytical.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row-level validation failure
- Missing required fields (row_id, company_group, date) causes schema rejection
- Numeric values outside allowed range (-1e12 to 1e12) rejected
- Invalid enum value for field or method parameters causes bad request error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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