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Label Review Analytics: Category Frequencies + Date by Category Pivot
x402
Label Review Analytics: Category Frequencies + 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 2026-10-24).
Computes category frequency counts and a date-by-category pivot table for label review records (reviewed_records, changed_labels) on up to 200 supplied rows — two independent analytical reports in one call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Category frequencies + Date by category pivot: Category frequencies + 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 separate analytical reports: (1) a category frequency table showing how often each dataset_group appears in the supplied rows, and (2) a date-by-category pivot table cross-tabulating the selected metric (reviewed_records or changed_labels) by date and dataset_group — both computed locally on the supplied data, no external lookups.
Example use cases
ML annotation QA category breakdown
“I have label review records from our annotation pipeline — each row has a date, a dataset group like 'group-a' or 'group-b', and counts of reviewed_records and changed_labels. Can you give me a frequency table of how often each category appears and a pivot of reviewed_records by date and category?”
Daily label change tracking per team
“Our QA team reviews datasets daily. I have about 80 rows of review logs with dates, group names, and changed_labels counts. Run the category frequency and date-by-category pivot reports on changed_labels so I can see which groups are changing the most labels each day.”
Audit of multi-group review coverage
“I need to audit our label review coverage across dataset groups. Here are 120 rows with row IDs, dates, dataset groups, and reviewed_records counts — can you generate the category frequency breakdown and the date-by-category pivot for reviewed_records?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-110?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation QA data with category/group labels and want both a frequency distribution of categories and a date-by-category pivot in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want local, deterministic computation without any live data fetch or external model inference. Prefer this over general BI tools when you need a quick, structured two-report summary of reviewed_records or changed_labels across dataset groups.
Side effects
- Submitting more than 200 rows returns an error or truncated results
- Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) cause validation failure
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Null values in numeric fields may affect aggregation accuracy
- Invalid field selector (not 'reviewed_records' or 'changed_labels') causes an error
- Empty rows array (minItems:1 not met) returns a validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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