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Time Series Completeness — Grouped Numeric Summary + Two-Measure Correlation
x402
Time Series Completeness — Grouped Numeric Summary + Two-Measure Correlation 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).
Analyzes supplied time series completeness records (observed_points, expected_points) by producing a grouped numeric summary and a two-measure correlation report for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Grouped numeric summary + Two-measure correlation: Grouped numeric summary + Two-measure correlation 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 grouped numeric summary breaking down observed_points or expected_points statistics by dataset_group, and (2) a two-measure correlation between observed_points and expected_points across the supplied rows. Both reports are computed locally on the submitted data with no external lookups.
Example use cases
Data pipeline completeness audit
“I've got daily completeness records for two pipeline groups, group-a and group-b, from October 2026 — each row has observed and expected data points. Can you give me a grouped numeric summary and a correlation between observed_points and expected_points across all 4 rows?”
Monitoring dashboard stats for sensor feeds
“We track sensor feed completeness every day, and I have 120 rows with date, sensor_group, observed_points, and expected_points. Run a grouped numeric summary and a two-measure correlation on this data so I can see which groups are falling behind.”
Weekly data quality review across teams
“Each team logs their observed vs expected data points daily — I have 80 rows grouped by team name, with dates from last month. Can you compute a grouped numeric summary and a correlation report for observed_points vs expected_points so we can review completeness at our weekly meeting?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-095?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of time series completeness data (observed vs expected point counts) and need both grouped descriptive statistics and a two-measure correlation in a single low-cost call ($0.01 USDC). It is ideal for lightweight, self-contained statistical analysis on supplied data without needing live lookups, predictions, or external integrations.
Side effects
- Input rows array is empty or missing — returns validation error
- More than 200 rows submitted — rejected by maxItems constraint
- Row missing required fields (row_id, dataset_group, date, observed_points, expected_points) — row-level validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric fields outside allowed range (-1000000000000 to 1000000000000) — validation error
- All observed_points or expected_points are null — correlation computation may be undefined or return NaN
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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