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Sampling Observations — Daily Sum + Secondary-Measure Weighted Mean
x402
Sampling Observations — Daily Sum + 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 for up to 200 supplied sampling observation records (sample_value, sample_weight).
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Daily sum series + Secondary-measure weighted mean: Daily sum series + Secondary-measure weighted mean for supplied sampling observations records (sample_value, sample_weight). 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 series aggregating sample_value (or sample_weight) by date, and (2) a secondary-measure weighted mean across the supplied rows, computed locally without any external lookup or prediction.
Example use cases
Daily sales volume rollup
“I have 150 daily sales sample records with values and weights — can you compute the daily sum series and the secondary-measure weighted mean so I can see how volume accumulates over time?”
Survey response aggregation
“I've got survey responses with sample values and response weights across two groups over the past month — please run the daily sum series and weighted mean report on all 80 rows using sample_value as the field.”
Sensor reading summary by day
“Here are 200 sensor readings from October, each tagged with a date, a group, a measurement value, and a confidence weight — give me the daily sum totals and the weighted average across the secondary measure.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-142?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have up to 200 tabular observation records with numeric values and weights keyed by date and group, and need both a daily sum time series and a weighted mean in a single low-cost call ($0.01 USDC). Prefer it over general-purpose analytics when you want two pre-defined statistical reports (sum series + weighted mean) computed from user-supplied data without any external data fetching, live lookups, or ML predictions.
Side effects
- More than 200 rows supplied — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern rejected
- sample_value or sample_weight outside ±1,000,000,000,000 bounds cause schema rejection
- Empty rows array (minItems: 1) returns error
- Invalid field enum value (not 'sample_value' or 'sample_weight') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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