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Schema Conformity Analytics: Trailing Mean Series + Date by Category Pivot
x402
Schema Conformity 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 2026-10-14).
Computes a trailing moving-average time series and a date-by-category pivot table for schema conformity data (valid_records, checked_records) in a single API call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Schema conformity — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot for supplied schema conformity records (valid_records, checked_records). 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 analytical reports: (1) a trailing moving-average time series for the chosen field (valid_records or checked_records) over the specified window size, and (2) a date-by-category pivot table grouping the same field values by date and dataset_group — both derived from the up-to-200 supplied rows, with no external data lookups.
Example use cases
Data pipeline quality trend monitoring
“I want to track how our valid_records are trending over the past week across two dataset groups, 'prod-pipeline' and 'staging-pipeline'. Can you compute a trailing mean with a window of 3 and also pivot the results by date and group? Here are my 10 rows of daily conformity data.”
Compliance audit schema conformity summary
“For our compliance audit I need both a rolling average and a date-by-category breakdown of our checked_records across the 'finance' and 'hr' dataset groups. Use a window of 5 and here are the 50 conformity records for last month.”
Comparing valid vs checked records across teams
“Can you analyze our schema conformity logs for the 'team-alpha' and 'team-beta' groups? I want a trailing mean series using a window of 4 on the checked_records field, plus a pivot table by date and category — I have about 30 rows covering the past month.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-02-152?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a rolling/trailing mean time series AND a pivot-by-category breakdown of schema conformity metrics (valid_records or checked_records) in a single low-cost call. It is ideal for data quality monitoring, governance reporting, or compliance workflows where you supply your own data (up to 200 rows) and need local analytical computation without any external lookups or predictions.
Side effects
- Fewer than 1 row or more than 200 rows supplied returns a validation error
- Window size less than 2 or greater than 200 is rejected
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Missing required fields (row_id, dataset_group, date, valid_records, checked_records) cause request failure
- Field enum value other than 'valid_records' or 'checked_records' is rejected
- Numeric values outside ±1,000,000,000,000 are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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