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Time Series Completeness — Exact Row Deduplication + Numeric Interval Filter
x402
Time Series Completeness — Exact Row Deduplication + Numeric 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).
Deduplicates exact rows and filters by numeric interval in time series completeness records (observed_points, expected_points) for up to 200 rows, producing 2 analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Exact row deduplication + Numeric interval filter: Exact row deduplication + 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 2 analytical reports derived from the submitted rows: one showing exact row deduplication results (unique vs duplicate rows identified) and one showing rows filtered by the specified numeric interval on the chosen field (observed_points or expected_points). No external data is fetched; all analysis is performed on the supplied rows only.
Example use cases
Daily pipeline completeness audit
“I have 120 time series completeness records from my daily data pipeline — each has a row_id, dataset_group, date, observed_points, and expected_points. Can you deduplicate exact duplicate rows and then filter to only keep rows where observed_points is between 0 and 500?”
Sensor data gap detection cleanup
“Here are my sensor completeness records for October — about 80 rows with observed_points and expected_points per day per sensor group. Please remove any exact duplicate entries and filter out rows where expected_points falls outside the range of 1 to 1000.”
Multi-group completeness report prep
“I need to prepare two analytical reports on these 200 time series completeness rows across multiple dataset groups — first deduplicate exact rows, then filter so only records where observed_points is between 10 and 200 are included. Can you run both on the same dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-043?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both exact row deduplication and numeric range filtering applied to time series completeness data (observed_points / expected_points) in a single low-cost call. It is ideal for lightweight local analytical checks on batches up to 200 rows without requiring any external data lookup, prediction, or live service. Prefer it over general-purpose data tools when your data is already structured with row_id, dataset_group, date, and numeric completeness fields.
Side effects
- Submitting more than 200 rows results in validation rejection
- Missing required fields (row_id, date, observed_points, expected_points) causes row-level errors
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- minimum greater than maximum produces an empty or nonsensical filter result
- Null numeric values may be excluded from interval filtering
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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