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Time Series Completeness — Numeric Row Ordering + Base-100 Series
x402
Time Series Completeness — Numeric Row Ordering + Base-100 Series 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 base-100 indexed series for up to 200 time series completeness records (observed vs expected points), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric row ordering + Base-100 series: Numeric row ordering + Base-100 series 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 reports: (1) a numeric row ordering ranking each input row by the selected field value, and (2) a base-100 indexed series anchored at the specified base_index row — all computed locally from the supplied rows without any external data lookups.
Example use cases
Pipeline completeness monitoring report
“I'm tracking data pipeline completeness across two groups for the past week — each day has observed and expected point counts. Can you rank all the rows by observed_points and give me a base-100 index series starting from row 0 so I can see relative completeness trends?”
Dataset group benchmarking with base index
“I have 30 rows of completeness data across multiple dataset groups with observed and expected points per date. Please produce a numeric row ordering and a base-100 series on expected_points anchored at row 5 so I can benchmark each group against that baseline.”
Anomaly detection prep via completeness indexing
“Before running anomaly detection, I need to normalize my 120-row time series completeness dataset. Can you give me numeric row ranks and a base-100 index on observed_points starting from row 0 so I can spot where completeness drops below baseline?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-117?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 time series completeness records with observed and expected point counts and need both a numeric rank ordering and a base-100 normalized index series in a single call. It is ideal for offline/batch analytical prep steps where no live data lookup, external enrichment, or prediction is needed — just deterministic ranking and indexing of supplied data at low cost ($0.01 per call for two reports).
Side effects
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, observed_points, expected_points) on any row
- Invalid date format (must be YYYY-MM-DD)
- base_index out of range for the number of supplied rows
- Null values for both observed_points and expected_points preventing computation
- Field enum value not in ['observed_points','expected_points']
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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