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Label Review Analytics: Adjacent Row Changes + Date by Category Pivot
x402
Label Review Analytics: Adjacent Row Changes + 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).
Runs two analytical reports on label review data: row-over-row change detection and a date-by-category pivot, for up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Adjacent row changes + Date by category pivot: Adjacent row changes + 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
Two analytical reports: (1) an adjacent row changes report showing sequential deltas for the selected metric (reviewed_records or changed_labels) across the supplied rows, and (2) a date-by-category pivot table aggregating the selected metric by date and dataset_group. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
ML labeling session trend analysis
“I have 80 rows of label review logs with columns row_id, dataset_group, date, reviewed_records, and changed_labels — can you compute the row-over-row changes and also pivot them by date and category so I can see which groups had the most activity each day? Focus the analysis on changed_labels.”
Data quality audit for label pipelines
“Run a two-part analysis on my label review records: first show me how reviewed_records change between adjacent rows, and then give me a pivot table grouped by date and dataset_group. I have about 120 rows to send.”
Daily review throughput breakdown by team
“I want to understand our daily label review throughput across teams — can you take these 60 review records with date, dataset_group, reviewed_records, and changed_labels, and give me both a sequential row-change report and a date-by-category pivot for reviewed_records?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-160?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both sequential row-change analysis and a date-by-category pivot on label review data in a single low-cost call. It is purpose-built for label review datasets (reviewed_records, changed_labels) and handles up to 200 rows with two independent analytical views for $0.01. Prefer it over general analytics tools when you want fast, offline computation on your own supplied data without any external API calls or ML predictions.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause validation failure
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Null numeric values may affect delta and aggregation calculations
- field enum value must be exactly 'reviewed_records' or 'changed_labels'
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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