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Time Series Completeness — Numeric Interval Filter + Daily Sum Series
x402
Time Series Completeness — Numeric Interval Filter + 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 2026-10-15).
Filters time series completeness records by a numeric interval and generates a daily sum series from observed/expected point data, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric interval filter + Daily sum series: Numeric interval filter + 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: (1) a numeric interval filter report listing records where the chosen field (observed_points or expected_points) falls within the specified minimum-maximum range, and (2) a daily sum series aggregating values by date. Both reports cover the supplied input rows (up to 200), computed using local analytical engines with no external data lookup.
Example use cases
Data pipeline completeness audit
“I need to audit my pipeline's completeness records for October — I have up to 50 rows with observed_points and expected_points per day across two groups. Filter observed_points between 0 and 100 and give me the daily sum series so I can see where totals spike.”
Threshold breach investigation
“Can you check which of my completeness records have expected_points between 10 and 500? I have about 80 rows across dataset groups 'sensor-a' and 'sensor-b' with dates in November 2026 — and also give me the daily sum breakdown for expected_points.”
Multi-group daily aggregation report
“I have 120 time series completeness rows across four dataset groups for Q4 2026, each with observed and expected point counts. Run both the numeric interval filter (observed_points from 0 to 50) and the daily sum series on this data so I can see day-by-day totals alongside the filtered subset.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-125?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two specific analytics on time series completeness data in a single low-cost call: a numeric interval filter and a daily sum aggregation. It is ideal for data quality monitoring workflows where you want to see both which records fall within a value range and how totals accumulate per day, without needing live lookups or predictive modeling. Best suited for batch completeness records up to 200 rows billed at a flat $0.01 USDC.
Side effects
- More than 200 rows submitted — request is rejected with a validation error
- Invalid date format (not YYYY-MM-DD) in any row causes a schema validation failure
- Missing required row fields (row_id, date, observed_points, expected_points) causes rejection
- Minimum value greater than maximum value may produce empty filter results or an error
- Null values in observed_points or expected_points may be excluded from sum calculations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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