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Label Review Analytics: Exact Row Deduplication + Equal-Width Histogram
x402
Label Review Analytics: Exact Row Deduplication + Equal-Width Histogram 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).
Deduplicates label review records by exact row matching and generates an equal-width histogram for a chosen numeric field (reviewed_records or changed_labels) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Exact row deduplication + Equal-width histogram: Exact row deduplication + Equal-width histogram 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 reports: (1) a deduplicated set of label review rows after exact row matching, indicating which rows were removed as duplicates; (2) an equal-width histogram for the specified numeric field (reviewed_records or changed_labels) showing bin boundaries and frequency counts across the configured number of bins.
Example use cases
Cleaning annotation pipeline audit logs
“I've got a CSV of label review sessions from our annotation team — up to 120 rows with row_id, date, dataset_group, reviewed_records, and changed_labels. Can you strip out any exact duplicate rows and then show me a histogram of changed_labels split into 10 equal-width bins?”
QA check on multi-group dataset review
“We ran label reviews across two dataset groups and ended up with 80 rows, but I suspect there are duplicates. Can you deduplicate them exactly and generate a 5-bin histogram of reviewed_records so I can see the distribution?”
Profiling label churn across review dates
“I have 200 rows of daily label review records and I want to understand how changed_labels are distributed. Please deduplicate first using exact row matching, then give me an equal-width histogram with 15 bins for changed_labels.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-048?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation audit data (up to 200 rows) and need both exact duplicate removal and a histogram profile of a numeric field in a single low-cost call. It is purpose-built for the reviewed_records/changed_labels schema, making it faster and cheaper than general-purpose ETL tools for this specific data shape. Prefer it over sibling endpoints when you need histogram output specifically (not category frequencies, outlier flags, or weighted means).
Side effects
- Exceeding 200 rows returns a validation error
- Invalid date format (not YYYY-MM-DD) causes row rejection
- Null values in the target histogram field may reduce effective bin coverage
- bins value outside 1–30 range causes schema validation failure
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause row-level errors
- Non-numeric values in numeric fields cause parse failures
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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