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Aggregation Checks — String Normalisation + Secondary-Measure Weighted Mean
x402
Aggregation Checks — String Normalisation + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Performs string normalisation and secondary-measure weighted mean calculations on up to 200 supplied aggregation check records containing source_sum and aggregate_sum fields, returning 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean 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 2 independent analytical reports: one covering string normalisation results across the supplied rows and one covering the secondary-measure weighted mean calculation for the selected field (source_sum or aggregate_sum), computed locally without any external lookups or predictions. Covers up to 200 input rows per call.
Example use cases
Reconcile monthly revenue aggregation data
“I have 50 rows of monthly revenue data with source_sum and aggregate_sum values across two dataset groups — can you run string normalisation and a weighted mean on the source_sum field to spot any aggregation inconsistencies?”
Data quality audit for BI pipeline
“Before I push these 120 aggregation check records into our BI pipeline, can you normalise the string fields and compute a secondary-measure weighted mean on aggregate_sum so I have two clean analytical reports to review?”
Compare group-level weighted averages
“I've got audit records from group-alpha and group-beta across Q3 dates with source_sum and aggregate_sum columns — run the string normalisation and weighted mean reports on source_sum so I can compare weighted averages between the two groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to apply both string normalisation and weighted mean analytics together on batch aggregation check data (up to 200 rows) in a single low-cost call. It is ideal for reconciliation workflows comparing source_sum against aggregate_sum across date-grouped records where no external data lookups or predictions are needed. Prefer this over general-purpose analytics services when you specifically need the dual-report output (normalisation + weighted mean) in one transaction for under $0.01 USDC.
Side effects
- Input array is empty or exceeds 200 rows — validation error returned
- Required fields (row_id, dataset_group, date, source_sum, aggregate_sum) missing from any row — schema validation failure
- Date field does not match YYYY-MM-DD pattern — rejected with pattern error
- Numeric values outside ±1,000,000,000,000 range — rejected
- Invalid field enum value (not source_sum or aggregate_sum) — rejected
- Payment not included or insufficient USDC — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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