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Time Series Completeness — Numeric Row Ordering + Secondary-Measure Weighted Mean
x402
Time Series Completeness — Numeric Row Ordering + 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 numeric row ordering and secondary-measure weighted mean analytics on time series completeness records (observed_points vs expected_points) for up to 200 rows, returning two independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric row ordering + Secondary-measure weighted mean: Numeric row ordering + Secondary-measure weighted mean for supplied time series completeness records (observed_points, expected_points). 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 numeric row ordering of the submitted completeness records, and (2) a secondary-measure weighted mean computed over the specified field (observed_points or expected_points), both derived from the supplied rows without any external lookup or prediction.
Example use cases
Daily pipeline completeness audit
“I have a list of daily ETL runs with observed_points and expected_points for each dataset group from last month — can you rank the rows numerically and compute the weighted mean on observed_points so I can see where coverage is lagging?”
Sensor data gap detection
“Here are 150 rows of sensor readings with observed and expected data points per day across several device groups. Run the row ordering and weighted mean analysis on expected_points so I can identify which days have the worst relative gaps.”
Multi-group completeness benchmarking
“I want to compare completeness across my dataset groups — I have 80 rows with dates, observed_points, and expected_points. Give me both the numeric row ordering and a secondary-measure weighted mean on observed_points so I can benchmark each group.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-121?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two simultaneous statistical reports — numeric row ordering plus weighted mean — on time series completeness records (observed vs expected data points) for up to 200 rows, all computed locally without external data lookups. Prefer this over single-report analytics endpoints when both ranking and weighted aggregation are needed in a single $0.01 call.
Side effects
- Exceeds 200-row limit — request rejected or truncated
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Null values in observed_points or expected_points may affect weighted mean accuracy
- Invalid field enum value (not 'observed_points' or 'expected_points') — rejected
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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