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Null Coverage Analytics: Row Deduplication + IQR Outlier Flags
x402
Null Coverage Analytics: Row Deduplication + 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 2026-10-14).
Deduplicates exact rows and flags IQR-based outliers in null coverage data (missing_values, total_values) for up to 200 supplied records, returning 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags for supplied null coverage records (missing_values, total_values). 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
Returns 2 independent analytical reports: one identifying exact duplicate rows in the supplied dataset and one flagging rows whose selected field (missing_values or total_values) falls outside the interquartile range (IQR) bounds, all computed locally without external lookups.
Example use cases
Data pipeline null coverage audit
“I've got 150 rows of null coverage data from our ETL pipeline — each has a row_id, dataset_group, date, missing_values, and total_values. Can you deduplicate any exact duplicate rows and flag which ones are IQR outliers on the missing_values field? I need 2 separate analytical reports.”
Detecting anomalous total_values across groups
“Here are 80 null coverage records across several dataset groups. Please deduplicate exact rows and run IQR outlier detection on the total_values field — I want to know which records are statistical anomalies.”
Pre-merge data quality check
“Before I merge these dataset quality logs, can you check for exact duplicate rows and flag any rows where missing_values is an IQR outlier? There are about 60 records, each with a row_id, group name, date, missing_values, and total_values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-049?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical deduplication and IQR-based outlier detection specifically on null coverage metrics (missing_values, total_values) for up to 200 rows, and you do not need live lookups, predictions, or external data enrichment. It is ideal for data quality audits, pre-merge checks, or ETL pipeline validation where two independent reports (dedup + outlier) are needed in a single low-cost call.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds limit
- Missing required fields (row_id, date, missing_values, total_values) — validation error
- Date field in wrong format (not YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range — schema rejection
- All rows are unique with no outliers — reports returned but empty flagged sets
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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