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Label Review Analytics: Category Frequencies + Missing-Value Fill
x402
Label Review Analytics: Category Frequencies + 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 2026-10-24).
Computes category frequency distributions and fills missing values (zero/mean/median) for label review records containing reviewed_records and changed_labels fields, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Category frequencies + Explicit missing-value fill: Category frequencies + 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
Returns two independent analytical reports: (1) a category frequency table showing how often each dataset_group value appears across the supplied rows, and (2) the specified numeric field (reviewed_records or changed_labels) with missing (null) values filled using the chosen method (zero, mean, or median). No external lookups or predictions are made; all computation is local.
Example use cases
Annotation audit frequency analysis
“I've got 150 label review rows from our NLP annotation project with dataset_group, date, reviewed_records, and changed_labels fields. Can you run a category frequency report so I can see how many records fall into each group, and fill any missing reviewed_records values using the mean?”
Missing label count imputation
“Our QA export has some null changed_labels entries scattered across dates in October 2026. Can you analyze the category frequencies across dataset groups and fill those missing changed_labels values with zeros so we can proceed with reporting?”
Multi-group label change distribution
“I have daily label review data for group-a and group-b from last quarter — up to 200 rows — and I need two reports: one showing how many records fall in each category group, and one with median fill for any missing reviewed_records values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-112?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular label review data (up to 200 rows) with dataset_group categories and numeric reviewed_records/changed_labels fields, and need both a frequency breakdown of categories AND missing-value imputation in a single paid call. It is ideal for ML/annotation pipeline QA steps where you need lightweight local analytics without sending data to an external prediction or live-lookup service.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, reviewed_records, changed_labels) in any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Invalid fill method or field enum value — rejected with enum mismatch error
- All values in target field are null — mean/median fill may be undefined or return zero
- Payment of 0.01 USDC not completed — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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