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Label Review Analytics: IQR Outlier Flags + Date-by-Category Pivot
x402
Label Review Analytics: 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 2026-10-15).
Analyzes label review records to detect IQR-based outliers and produce a date-by-category pivot table, returning two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot for supplied label review records (reviewed_records, changed_labels). 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 independent reports: (1) an IQR outlier flag report identifying which rows have values outside the interquartile range for the selected field (reviewed_records or changed_labels), and (2) a date-by-category pivot table summarizing the selected metric grouped by date and dataset_group. All analysis is performed locally on the supplied data with no external lookups.
Example use cases
Annotation QA spike detection
“I have 150 rows of label review logs with row_id, dataset_group, date, reviewed_records, and changed_labels — can you flag any IQR outliers in changed_labels and also give me a pivot of activity by date and group?”
ML pipeline audit by team
“We ran a week of labeling across three dataset groups and I want to know which days or groups had abnormally high reviewed_records counts — run IQR outlier flags and a date-by-category breakdown on the data I'm sending you.”
Label quality review summary
“Here's my label review export with up to 200 records across multiple dataset groups — please detect outliers using IQR on the reviewed_records field and generate a pivot table showing totals by date and category.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-178?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based outlier detection and a date-by-category pivot on label review records in a single low-cost call. It is purpose-built for annotation QA workflows where you have up to 200 rows with reviewed_records and changed_labels metrics segmented by dataset group and date. Prefer it over generic analytics tools when you want two bundled reports at $0.01 USDC without any external lookups or live data dependencies.
Side effects
- Input array is empty or contains more than 200 rows — request rejected
- Missing required fields (row_id, date, dataset_group, reviewed_records, changed_labels) on any row — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- All values for the selected field are null — IQR computation not possible
- Field selector not one of 'reviewed_records' or 'changed_labels' — enum validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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