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Duplicate Observations Analytics: Duplicate Key Report + Trailing Mean Series
x402
Duplicate Observations Analytics: Duplicate Key Report + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Analyzes supplied duplicate observation records to produce a duplicate key report and a trailing mean series for up to 200 rows, using local analytical engines with no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Duplicate key report + Trailing mean series: Duplicate key report + Trailing mean series 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 duplicate key report identifying duplicate row patterns and counts across the supplied records by dataset group and key fields, and (2) a trailing mean series computed over the selected field (duplicate_rows or total_rows) using the specified rolling window size. Both reports are computed locally with no external data access, covering up to 200 input rows.
Example use cases
Data pipeline duplicate rate audit
“I have 50 rows of daily ingestion records for three dataset groups from the past two months, each with duplicate_rows and total_rows counts. Can you run a duplicate key report and compute a trailing mean series for duplicate_rows with a window of 7 so I can see the rolling trend?”
Data quality dashboard for ETL monitoring
“Here are 120 records from our ETL jobs — each has a date, dataset_group, duplicate_rows, and total_rows. Generate a duplicate key report and a trailing mean series for total_rows using a window of 10, so we can monitor data quality over time.”
Spot-check duplicate spike investigation
“We had some suspicious duplicate spikes last week across two dataset groups. I have 30 rows with row_id, date, dataset_group, duplicate_rows, and total_rows. Please produce a duplicate key report and a trailing mean series on duplicate_rows with a window of 3 to help me see where the anomalies cluster.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-061?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected duplicate observation records (with duplicate_rows and total_rows counts per date and dataset group) and need both a structural duplicate key report and a temporal trailing mean series in a single low-cost call. Ideal for data quality audits, ETL monitoring, and pipeline health checks where no live data lookup or external enrichment is needed and the dataset fits within 200 rows.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) cause validation errors
- Date values not matching YYYY-MM-DD pattern result in schema rejection
- Window value outside 2–200 range causes parameter error
- Null values in numeric fields may affect trailing mean computation
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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