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Time Series Completeness — Grouped Numeric Summary + Daily Sum Series
x402
Time Series Completeness — Grouped Numeric Summary + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Analyzes time series completeness data by producing a grouped numeric summary and a daily sum series for observed vs. expected data points, across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Grouped numeric summary + Daily sum series: Grouped numeric summary + Daily sum 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 analytical reports computed from the supplied rows: (1) a grouped numeric summary of the selected field (e.g. observed_points) broken down by dataset_group, and (2) a daily sum series showing totals per date. Both reports use local analytical engines with no external data access, covering up to 200 input rows.
Example use cases
IoT sensor coverage audit by device group
“I have daily completeness records for two IoT device groups — 'sensors-north' and 'sensors-south' — showing observed vs expected readings for each day in October 2026. Can you give me a grouped numeric summary and daily sum series for the observed_points field so I can see which group is missing the most data?”
Data pipeline completeness dashboard
“My ETL pipeline tracks observed and expected records per day for three dataset groups: 'raw-events', 'processed-events', and 'aggregated-events'. I have 90 rows of completeness data. Can you compute both a grouped numeric summary and a daily sum series on the expected_points field so I can spot gaps?”
Multi-tenant SLA completeness reporting
“I need to report on data completeness for 5 client groups across the past month — I have up to 150 rows with date, dataset_group, observed_points, and expected_points. Please generate a grouped numeric summary and daily sum series using observed_points so I can share the completeness breakdown with each tenant.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-089?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a grouped statistical summary and a daily aggregate series for time series completeness data (observed vs. expected points) in a single low-cost call. It is ideal for data quality monitoring, pipeline audits, and SLA reporting across multiple dataset groups without requiring any external data lookups or predictions. Prefer it over general-purpose analytics when your data fits the completeness schema (row_id, dataset_group, date, observed_points, expected_points) and you need exactly these two report types for up to 200 rows at $0.01.
Side effects
- Fewer than 1 row supplied — minItems constraint violation
- More than 200 rows supplied — maxItems constraint violation
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) on any row
- Invalid date format not matching YYYY-MM-DD pattern
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)
- Invalid field enum value (must be 'observed_points' or 'expected_points')
- Payment failure — 0.01 USDC required per call
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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