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Aggregation Checks — Trailing Mean Series + Date by Category Pivot
x402
Aggregation Checks — 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 2026-10-24).
Computes a trailing moving-average time series and a date-by-category pivot table for aggregation check records containing source_sum and aggregate_sum fields, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot for supplied aggregation checks records (source_sum, aggregate_sum). 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 trailing moving-average time series for the selected field (source_sum or aggregate_sum) computed over the specified window size, and (2) a date-by-category pivot table breaking down values by dataset_group across dates — both derived solely from the supplied input rows (up to 200).
Example use cases
Reconciliation trend check for finance team
“I have 150 rows of daily reconciliation records with source_sum and aggregate_sum across three dataset groups from Q3. Can you run the trailing mean series with a window of 7 and a date-by-category pivot on source_sum so I can spot where the aggregations diverge?”
Weekly ETL pipeline aggregation audit
“After each ETL run I need to validate my aggregation sums — I have 80 rows tagged by dataset_group and date. Run a trailing mean series with window 5 and a date pivot on aggregate_sum so I can see group-level patterns over time.”
Data quality review for monthly reporting
“I'm preparing a monthly data quality report and need two things: a rolling mean trend for source_sum with a 3-row window, and a date-by-category pivot grouping my 60 aggregation check records by dataset_group. Can you produce both?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-152?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a rolling/trailing mean time series AND a date-by-category pivot table computed together on aggregation check records (source_sum, aggregate_sum) in a single paid call. It is purpose-built for reconciliation and aggregation validation workflows where you supply your own data and want offline analytical summaries — not for live lookups, predictions, or external data enrichment.
Side effects
- Fewer than 1 row supplied — request rejected by minItems constraint
- Window size larger than number of rows — trailing mean series may be empty or partial
- Invalid date format (not YYYY-MM-DD) — schema validation error
- source_sum or aggregate_sum values outside ±1,000,000,000,000 — rejected by schema bounds
- row_id or dataset_group exceeding 80 characters — schema validation error
- More than 200 rows supplied — rejected by maxItems constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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