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Aggregation Checks — Daily Sum Series + Secondary-Measure Weighted Mean
x402
Aggregation Checks — Daily Sum Series + 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 2026-10-15).
Computes a daily sum time series and a secondary-measure weighted mean over up to 200 supplied aggregation check rows (source_sum, aggregate_sum), returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — Daily sum series + Secondary-measure weighted mean: Daily sum series + 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 two analytical reports: (1) a daily sum time series aggregating the selected field (source_sum or aggregate_sum) by date across all supplied rows, and (2) a secondary-measure weighted mean report. Both reports are computed locally from the supplied data (up to 200 rows) with no external lookups or live data sources.
Example use cases
Daily revenue aggregation validation
“I have 150 rows of daily sales aggregation checks with source_sum and aggregate_sum for each date from 2025-01-01 to 2025-05-31 across two dataset groups — can you compute the daily sum time series and weighted mean on the source_sum field so I can spot where totals diverge?”
Weekly ETL pipeline audit
“Run the daily sum series and secondary-measure weighted mean on these 80 aggregation records from my ETL pipeline — dates range from 2025-06-01 to 2025-08-19, I have source_sum and aggregate_sum per row across groups 'raw' and 'processed', and I want to use aggregate_sum as the field for the weighted mean.”
Group-level data quality check
“I need to audit two dataset groups — 'north' and 'south' — using 60 daily aggregation rows from Q1 2025. Each row has a source_sum and aggregate_sum. Please give me the daily sum series and the secondary-measure weighted mean using source_sum so I can see which group has the bigger discrepancy.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-142?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular aggregation check data with source_sum and aggregate_sum columns and need both a daily sum time series and a weighted mean in a single $0.01 call. It is ideal for data quality audits, ETL validation, or lightweight analytics on pre-supplied data without needing external data access or live lookups. Prefer it when your dataset is 200 rows or fewer and you want two reports bundled together cheaply.
Side effects
- Empty rows array — rejected if fewer than 1 row supplied
- Rows exceeding 200 — returns error if maxItems exceeded
- Invalid date format — must match YYYY-MM-DD pattern exactly
- source_sum or aggregate_sum out of range (beyond ±1,000,000,000,000) — rejected
- Missing required fields (row_id, dataset_group, date, source_sum, aggregate_sum) — validation error
- Invalid field enum value — only 'source_sum' or 'aggregate_sum' accepted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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