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Duplicate Observations Analytics: Grouped Summary + Dataset Comparison
x402
Duplicate Observations Analytics: Grouped Summary + Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Runs two offline analytical reports on duplicate_rows/total_rows data: a grouped numeric summary and a keyed dataset comparison between two supplied datasets (up to 200 rows each).
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Grouped numeric summary + Keyed dataset comparison: Grouped numeric summary + Keyed dataset comparison for supplied duplicate observations records (duplicate_rows, total_rows). 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 grouped numeric summary aggregating duplicate_rows or total_rows statistics by dataset_group, and (2) a keyed dataset comparison matching records by row_id across the primary and secondary datasets to highlight differences. No external lookups or predictions are made; all analysis uses locally supplied data.
Example use cases
ETL pipeline duplicate rate audit
“I have two ETL run snapshots with up to 100 rows each, tracking duplicate_rows and total_rows by dataset_group and date. Can you give me a grouped numeric summary across groups and then compare the two runs row by row to see where duplicate counts changed?”
Data quality report by dataset group
“Run a grouped numeric summary on this set of 80 duplicate observation records — I want to see the stats broken down by dataset_group using the duplicate_rows field, and also compare it against last week's snapshot with the same row keys.”
Cross-team dataset deduplication comparison
“We have two teams each submitting duplicate observation logs (about 60 rows each) with the same row_id keys. Can you analyze the total_rows field with a grouped summary and then do a keyed comparison between the two team datasets to spot discrepancies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-098?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have already-collected duplicate observation records (with duplicate_rows and total_rows counts) and need both a grouped statistical summary across dataset groups and a direct row-keyed comparison between two datasets in a single paid call. Ideal for data quality monitoring, ETL audit workflows, or comparing deduplication results across pipeline runs. Not suitable when you need live data fetching, predictions, or more than 200 rows per dataset.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) cause validation errors
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Null numeric values may affect aggregation results in the summary report
- Non-matching row_ids between primary and secondary datasets reduce keyed comparison coverage
- Both rows arrays must each individually comply with the 200-row limit
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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