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Label Review Analytics: Date-by-Category Pivot + Missing-Value Fill
x402
Label Review Analytics: Date-by-Category Pivot + Missing-Value Fill 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).
Generates two analytical reports from label review data: a date-by-category pivot table and an explicit missing-value fill, for up to 200 rows of reviewed_records and changed_labels data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill 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) a pivot table cross-tabulating the selected metric (reviewed_records or changed_labels) by date and dataset_group, and (2) the same dataset with missing values in the target field explicitly filled using the chosen method (zero, mean, or median). No external lookups or predictions are made — all computation is local and deterministic.
Example use cases
Annotation QA daily activity breakdown
“I have 80 rows of annotation review logs with dates, dataset groups, reviewed_records counts, and changed_labels — can you pivot them by date and group and fill any missing reviewed_records values with the median?”
Missing changed_labels imputation
“Some of my label review records are missing changed_labels values. Use zero-fill to plug those gaps and also give me a pivot of changed_labels by date and dataset_group across my 120 rows.”
ML dataset review summary report
“We track reviewed_records and changed_labels across multiple dataset groups daily. Can you build a date-by-group pivot table from our 150 review records and replace any null reviewed_records with the mean?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-189?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation quality data organized by date and category group, and need both a cross-tabulated summary (pivot) and missing-value imputation in a single low-cost call. Ideal for ML ops teams tracking reviewed_records and changed_labels across dataset partitions over time. Prefer this over general-purpose analytics tools when you want a deterministic, offline, no-side-effect report that delivers two complementary views of your review data at $0.01 per batch of up to 200 rows.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Invalid date format (must match YYYY-MM-DD pattern) — row will error or be rejected
- Missing required fields (row_id, date, dataset_group) — schema validation failure
- Numeric values outside allowed range (-1T to 1T) — validation error
- Empty rows array — minimum 1 item required
- Invalid fill method enum value — must be zero, mean, or median
- Invalid field enum value — must be reviewed_records or changed_labels
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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