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Duplicate Observations Analytics: Trailing Mean Series + Date by Category Pivot
x402
Duplicate Observations Analytics: Trailing Mean Series + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Computes a trailing mean time series and a date-by-category pivot table for duplicate-observation metrics (duplicate_rows, total_rows) across up to 200 supplied data rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot 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 computed from the supplied rows: (1) a trailing mean series over the chosen field (duplicate_rows or total_rows) using the specified window size, and (2) a date-by-category pivot table showing the field values broken down by date and dataset_group. Both reports are computed locally on the provided data without any external lookups.
Example use cases
Data quality trend monitoring
“I've been tracking duplicate rows in our nightly ETL pipeline across two dataset groups for the last 30 days — can you compute a trailing mean series (window of 7) on the duplicate_rows field and also pivot the data by date and group so I can spot which groups are getting worse over time?”
Weekly deduplication audit report
“Run a trailing mean and date-by-category pivot on total_rows for our four dataset groups using a window of 5 — here are the 20 rows from our weekly audit: group-a through group-d across dates 2026-09-01 to 2026-09-20, with total_rows ranging from 500 to 5000.”
Data governance dashboard analytics
“I need two reports on our duplicate observation data for the governance review: a rolling mean series with window 4 on duplicate_rows, and a pivot of duplicate counts by date and dataset category — I have 50 records across three groups spanning October 2026.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-152?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of duplicate observation records and need both a trailing moving average time series AND a date-by-category pivot in a single cost-efficient call ($0.01 USDC for both reports). It is ideal for data quality monitoring, ETL auditing, and governance dashboards where offline computation on supplied data is sufficient and no live lookup or external data is needed.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — exceeds maximum item limit
- Window size larger than number of rows — trailing mean may produce insufficient data points
- Invalid date format (not YYYY-MM-DD) — fails pattern validation
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — schema validation error
- Numeric values outside allowed range (-1T to +1T) — rejected
- Invalid field enum value — must be 'duplicate_rows' or 'total_rows'
- Payment failure — 0.01 USDC required per call via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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