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Aggregation Checks — Secondary-Measure Weighted Mean + Date by Category Pivot
x402
Aggregation Checks — Secondary-Measure Weighted Mean + 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 2026-10-15).
Computes a weighted mean on a secondary numeric measure and produces a date-by-category pivot table for up to 200 supplied aggregation-check rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — Secondary-measure weighted mean + Date by category pivot: Secondary-measure weighted mean + 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 analytic reports: (1) a secondary-measure weighted mean computed across the supplied rows using the selected field (source_sum or aggregate_sum), and (2) a pivot table breaking down values by date and dataset_group category. Both reports are derived exclusively from the supplied data with no external lookups.
Example use cases
Reconciliation weighted mean check
“I need to validate our monthly reconciliation data — I have 50 rows each with a source_sum and aggregate_sum tagged to dataset groups and dates. Can you compute the weighted mean on aggregate_sum and pivot the results by date and group so I can spot discrepancies?”
Category pivot for finance aggregation audit
“We're auditing aggregation totals across two business units. I have 120 rows with date, dataset_group, source_sum, and aggregate_sum. Run the weighted mean on source_sum and give me a date-by-category pivot so we can see how each group's sums break down over time.”
ETL output verification by group
“After our ETL pipeline ran, I have 80 rows of output data with source_sum and aggregate_sum per dataset_group and date. Can you calculate the weighted mean for source_sum and produce a pivot table by date and category to verify the output looks correct?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-185?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-assembled tabular aggregation-check records (with source_sum and aggregate_sum) and need both a weighted mean on a chosen numeric measure and a date-by-category pivot in a single low-cost call. It is ideal for reconciliation auditing, ETL validation, and business intelligence summarization on small-to-medium datasets (up to 200 rows) without requiring external data lookups or prediction.
Side effects
- Fewer than 1 row or more than 200 rows supplied — request rejected
- Missing required fields (row_id, dataset_group, date, source_sum, aggregate_sum) — validation error
- Date values not matching YYYY-MM-DD format — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — rejected
- All numeric values null — weighted mean undefined or returns null result
- Invalid field enum value — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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