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Time Series Completeness Analytics — Numeric Distribution & Interval Filter
x402
Time Series Completeness Analytics — Numeric Distribution & Interval Filter 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 time series completeness records (observed vs expected points) by computing numeric distribution statistics and filtering by a numeric interval, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric distribution + Numeric interval filter: Numeric distribution + Numeric interval filter 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 distribution summary (e.g. min, max, mean, percentiles, histogram buckets) for the selected field (observed_points or expected_points) across all supplied rows, and (2) a filtered subset of rows where the selected field falls within the specified minimum–maximum interval. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Daily pipeline completeness audit
“I have 120 rows of daily time series completeness records with observed_points and expected_points for two dataset groups — can you run a numeric distribution report on observed_points and also filter to rows where observed_points is between 50 and 500?”
Detecting data gaps in sensor feeds
“Here are my sensor feed completeness records for the last 90 days — row_id, date, group name, observed_points, expected_points. Can you compute the distribution of expected_points and filter it between 10 and 1000 so I can spot anomalies?”
QA check on ETL job output completeness
“I need to QA my ETL jobs — I've got 200 rows of completeness data per day with observed and expected point counts. Run a distribution analysis on observed_points and show me only the records where observed_points is between 0 and 200.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-074?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 distribution summary and an interval-filtered view in a single API call for $0.01 USDC. It is ideal for lightweight, local data-quality analytics without needing an external database, live data connection, or ML prediction service. Prefer alternatives if you need more than 200 rows, real-time data ingestion, predictive analytics, or non-numeric analysis.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds limit, request rejected
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — schema rejection
- Invalid field enum value (not 'observed_points' or 'expected_points') — validation error
- Payment of 0.01 USDC not included or declined — 402 payment required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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