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Time Series Completeness — Exact Row Deduplication + Numeric Distribution
x402
Time Series Completeness — Exact Row Deduplication + Numeric Distribution 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).
Runs two local analytical reports on time series completeness data: exact row deduplication and numeric distribution analysis for observed_points or expected_points, across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Exact row deduplication + Numeric distribution: Exact row deduplication + Numeric distribution 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 reports: (1) an exact row deduplication report identifying which rows among the submitted records are identical, and (2) a numeric distribution report (e.g. min, max, mean, quartiles, histogram bins) for the selected field (observed_points or expected_points), all computed locally without any external lookups.
Example use cases
Deduplicate daily completeness records
“I've got a list of up to 200 time series completeness rows with row_id, dataset_group, date, observed_points, and expected_points — can you run exact row deduplication on them and also show me the numeric distribution of observed_points?”
Distribution analysis for expected data points
“Here are my completeness tracking records across several dataset groups and dates. Can you analyze the numeric distribution of expected_points and also flag any exact duplicate rows in the data?”
Audit completeness logs for duplicates and spread
“I need to audit my time series completeness logs — I have about 50 rows with observed and expected point counts per date and group. Run deduplication and give me a distribution breakdown for observed_points so I can see if there are anomalies.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-039?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 time series completeness records and need both exact duplicate detection and numeric distribution analysis in a single low-cost call ($0.01 USDC for both reports). Ideal for data quality audits on completeness metrics (observed vs expected points) where no external lookup, live data, or predictive modeling is needed — pure local computation on supplied data.
Side effects
- More than 200 rows submitted — request rejected
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- field selector not one of 'observed_points' or 'expected_points' — enum validation error
- Empty rows array — minItems violation
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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