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Null Coverage IQR Outlier Flags + Date-by-Category Pivot
x402
Null 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 2026-10-14).
Analyzes up to 200 null-coverage records (missing_values, total_values) and returns two local analytical reports: IQR-based outlier flags and a date-by-category pivot table.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot 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 two analytical reports: (1) IQR outlier flags for each row indicating whether the selected field (missing_values or total_values) is an outlier based on interquartile range thresholds, and (2) a pivot table summarizing the selected field's values grouped by date and dataset_group category. All computation is performed locally with no external lookups.
Example use cases
Outlier detection in ETL pipeline audits
“I have audit records from my ETL jobs — each row has a dataset group, a date, and counts of missing vs total values. Can you flag which rows have outlier missing_values using IQR and also give me a pivot of missing_values by date and group?”
Monthly data quality review across teams
“Here are 120 null-coverage records from our three data teams for October 2026, each tagged with a dataset_group and date. Run the IQR outlier flags plus the date-by-category pivot on total_values so I can see which groups had unusual completeness numbers.”
Pre-release dataset validation report
“Before we ship this dataset, I need two reports on our null coverage stats — IQR-based outlier flags on missing_values and a date-by-category breakdown — here are the 80 rows with row_id, date, dataset_group, missing_values, and total_values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-178?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 null-coverage or data-completeness records and need both IQR-based outlier detection and a date-by-category pivot in a single low-cost call ($0.01 USDC). Ideal for data quality monitoring workflows, ETL audit reporting, or pre-release dataset validation where no external data enrichment or live lookup is needed — just fast, local analytical computation on your supplied records.
Side effects
- Fewer than 1 row submitted — minItems:1 violation returns validation error
- More than 200 rows submitted — maxItems:200 limit exceeded
- Invalid date format (not YYYY-MM-DD pattern) causes schema validation failure
- Non-numeric or out-of-range missing_values or total_values rejected by schema
- Missing required fields (row_id, dataset_group, date) cause per-row validation errors
- Insufficient row variance for meaningful IQR calculation with very small datasets
- Payment failure or insufficient USDC balance blocks request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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