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Company Filing Inventories — String Normalisation + IQR Outlier Flags
x402
Company Filing Inventories — String Normalisation + IQR Outlier Flags 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).
Runs string normalisation and IQR-based outlier detection on up to 200 rows of company filing inventory data (available_filings, expected_filings), returning two analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company filing inventories — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied company filing inventories records (available_filings, expected_filings). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two analytical reports: (1) a string normalisation report showing standardised company_group values and normalisation changes applied; (2) an IQR outlier flagging report identifying which rows have available_filings or expected_filings values that fall outside the interquartile range bounds, with outlier flag indicators per row.
Example use cases
Audit filing inventory anomalies
“I have a dataset of 150 company filing records with available_filings and expected_filings counts — can you flag any IQR outliers in the available_filings column and normalise the company_group strings for me?”
Clean regulatory filing data
“We've got messy company group names in our filing inventory export and some suspiciously high expected_filings numbers — run string normalisation and IQR outlier flagging on these 80 rows so we can identify what needs manual review.”
QA check on quarterly filings
“Before we submit our quarterly filing reconciliation, can you check these 200 rows of filing inventory data for string inconsistencies in company_group and detect any outlier values in the expected_filings field using IQR analysis?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-17-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and IQR outlier detection on company filing inventory data (available_filings or expected_filings) in a single cheap call ($0.01 USDC for two reports). It is ideal for data quality pipelines processing up to 200 filing records at a time without requiring live data lookups or external integrations. Prefer it over generic analytics tools when working specifically with company_group-keyed filing inventory structures.
Side effects
- Fewer than 1 row supplied — returns validation error
- More than 200 rows submitted — rejected with row limit error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Missing required fields (row_id, company_group, date) — rejected
- Numeric values outside allowed range (±1,000,000,000,000) — schema error
- Invalid field enum value — rejected with allowed values listed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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