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Company Headcount Observations — Record Quality Audit, String Normalisation & Missing-Value Fill
x402
Company Headcount Observations — 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 2026-10-19).
Audits record quality, normalises strings, and fills missing values in company headcount observation data (headcount, open_roles) for up to 200 rows, returning three independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied company headcount observations records (headcount, open_roles). 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, out-of-range values, and malformed records; (2) a string normalisation report identifying and correcting inconsistencies in company_group labels; and (3) an explicit missing-value fill report showing which headcount or open_roles values were imputed and with what value (zero, mean, or median).
Example use cases
Pre-analysis headcount data cleanup
“I have 120 rows of quarterly headcount observations across several company groups and I need to clean them up before analysis — can you audit the record quality, fix any inconsistent company_group labels, and fill missing headcount values using median imputation?”
Open roles data gap filling
“My open_roles data has a bunch of nulls scattered across dates and company groups — can you run a missing-value fill using mean substitution on the open_roles field and also give me a record quality report on the whole dataset?”
HR reporting pipeline data validation
“Before I send this headcount dataset to our reporting team, can you do a full quality audit, normalise the company name strings, and fill any missing headcount entries with zero so the downstream system doesn't break?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-208?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality audit, string normalisation, and missing-value imputation in a single call for company headcount datasets of up to 200 rows. It is ideal as a preprocessing step before downstream analytics or reporting, when you want three distinct reports from one $0.01 payment without any external lookups or live data enrichment.
Side effects
- Empty rows array or rows exceeding 200 items returns a validation error
- Invalid date format (not YYYY-MM-DD) causes row rejection
- Missing required fields (row_id, company_group, date) results in row-level errors
- Invalid enum values for field or method parameters return a schema validation error
- Payment not completed via x402 protocol results in 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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