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Business Directory Coverage IQR Outlier Flags + Date by Category Pivot
x402
Business Directory Coverage IQR Outlier Flags + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Runs two analytical reports on business directory coverage data: IQR-based outlier detection and a date-by-category pivot, for up to 200 rows of listed/verified entity counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Business directory coverage — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot for supplied business directory coverage records (listed_entities, verified_entities). 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 for the supplied dataset: (1) IQR outlier flags identifying rows where the selected field (listed_entities or verified_entities) falls outside the interquartile range bounds, and (2) a pivot table of the selected metric broken down by date and company_group category. Both reports cover up to 200 input rows and are computed locally without external lookups.
Example use cases
Spotting anomalous directory listings
“I've got 50 rows of daily business directory data by company group with listed_entities counts — can you run IQR outlier detection on listed_entities and also pivot the results by date and category so I can see which days or groups are out of the norm?”
Verifying data quality before reporting
“Before I send my quarterly directory coverage report, can you check my verified_entities figures across these company groups for IQR outliers and also generate a date-by-category breakdown? I want to catch any bad data points first.”
Monitoring coverage gaps across groups
“I track business directory coverage for group-a and group-b every day — can you analyze my last 30 days of listed_entities data, flag anything statistically unusual using IQR, and show me a pivot table grouped by date and category?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-14-178?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of business directory coverage data (listed and verified entity counts by company group and date) and need both IQR-based outlier flagging and a date-by-category pivot in a single low-cost call. It is ideal for data quality checks before reporting, anomaly detection in directory datasets, and summarizing coverage trends. It does not perform live lookups, predictions, or external enrichment — use it purely for local statistical analysis of supplied data.
Side effects
- Missing required fields (row_id, date, company_group) returns a validation error
- Fewer than 1 or more than 200 rows triggers a row count constraint error
- Invalid date format (non-YYYY-MM-DD) causes schema rejection
- Null or out-of-range numeric values for listed_entities or verified_entities may be excluded from IQR computation
- Invalid field enum value (not 'listed_entities' or 'verified_entities') returns an error
- Insufficient row variance may produce trivial or degenerate IQR results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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