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Company Headcount Observations — String Normalisation + IQR Outlier Flags
x402
Company Headcount Observations — 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 2026-10-19).
Normalises string fields and flags IQR-based outliers in company headcount and open-roles observation data for up to 200 rows, producing two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied company headcount observations records (headcount, open_roles). 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 independent analytical reports covering: (1) string normalisation results for the company_group field across the submitted rows, and (2) IQR outlier flags for the selected numeric field (headcount or open_roles), identifying which row IDs fall outside the interquartile range bounds. Up to 200 rows processed per call.
Example use cases
Flagging anomalous headcount spikes
“I've got 80 rows of monthly headcount observations across three company groups and I suspect some entries are statistical outliers — can you run IQR outlier detection on the headcount field and normalise the company group strings at the same time?”
Cleaning open roles data before reporting
“Before I publish our quarterly workforce report, can you normalise the string fields and flag any IQR outliers in the open_roles column across these 120 company headcount rows grouped by division?”
HR data quality audit across subsidiaries
“We've consolidated headcount data from five subsidiaries into about 200 rows — can you check the headcount field for IQR-based outliers and clean up any inconsistent string formatting in the company_group column so our records are consistent?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular company headcount or open-roles observations and need both string normalisation of categorical labels and statistical outlier detection (IQR method) in a single batch call. Ideal for HR analytics pipelines, workforce data quality audits, or pre-processing steps before dashboarding or reporting. Best when you have up to 200 rows and want two structured reports without building your own analytics logic.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, company_group, date, headcount, open_roles) cause row-level errors
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- All numeric values null prevents IQR calculation
- Single-row input may produce degenerate IQR results with no meaningful outlier detection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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