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Time Series Completeness — Numeric Row Ordering + Keyed Dataset Comparison
x402
Time Series Completeness — Numeric Row Ordering + Keyed Dataset Comparison 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 by performing numeric row ordering and keyed dataset comparison across up to 200 rows, producing two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric row ordering + Keyed dataset comparison: Numeric row ordering + Keyed dataset comparison 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 numeric row ordering report that sequences the supplied rows by their numeric values, and (2) a keyed dataset comparison report that matches rows between the primary and secondary datasets by key fields (row_id, dataset_group, date) to highlight differences in observed_points or expected_points. All analysis is performed locally on the supplied data with no external lookups.
Example use cases
Data pipeline completeness audit
“I need to check completeness of my data pipeline — here are my daily rows with observed_points and expected_points for group-a and group-b from October 2026. Can you run the numeric ordering and keyed comparison reports on observed_points to see where counts fall short?”
Comparing two dataset versions for drift
“I have two versions of the same time series dataset — the original and an updated one — each with observed_points and expected_points per date and group. Can you compare them side by side using the keyed dataset comparison so I can spot any differences between them?”
Validating sensor data completeness by group
“I'm tracking expected vs observed sensor readings across different groups over a 30-day period. Run me both the row ordering and keyed comparison reports on expected_points so I can see which groups are consistently underreporting.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-123?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to audit or validate time series completeness data by both ordering rows numerically and comparing two keyed datasets in a single $0.01 call. It is best suited for offline batch analysis of up to 200 pre-assembled rows where no live data lookup, prediction, or external enrichment is needed. Prefer this over general analytics platforms when you want a lightweight, low-cost dual-report on observed vs expected point counts across grouped time series data.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- No 'other' dataset provided when comparison report is expected — may return partial results
- Null values in numeric fields — may affect ordering or comparison calculations
- Payment of 0.01 USDC not completed — request blocked by x402 payment gate
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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