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Time Series Completeness — Duplicate Key Report + Numeric Interval Filter
x402
Time Series Completeness — Duplicate Key Report + 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).
Analyzes time series completeness records to produce a duplicate key report and a numeric interval filter report for observed/expected data points across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Duplicate key report + Numeric interval filter: Duplicate key report + 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 independent analytical reports: (1) a duplicate key report identifying rows with repeated row_id or key combinations within the supplied dataset, and (2) a numeric interval filter report listing rows where the selected numeric field (observed_points or expected_points) falls within the specified minimum–maximum range. Up to 200 input rows are processed locally with no external lookups.
Example use cases
Auditing completeness logs for duplicate entries
“I have a batch of 50 time series completeness records with row IDs, dataset groups, and daily observed vs expected point counts — can you run a duplicate key report on them to find any rows that share the same identifier?”
Filtering completeness data by observed point range
“From my time series completeness dataset, filter down to only the rows where expected_points is between 10 and 100 — I have about 80 records across group-a and group-b spanning October 2026.”
Data quality check before pipeline ingestion
“Before I ingest these 150 completeness records into our pipeline, can you check for any duplicate row IDs and also flag which rows have observed_points outside the range of 0 to 500 so I can clean them up first?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-059?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two simultaneous local analytical reports — a duplicate key check and a numeric range filter — on time series completeness data (observed vs expected points) without any external data lookups or predictions. It is ideal for data quality auditing of completeness logs before pipeline ingestion, at $0.01 USDC for both reports on up to 200 rows.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, dataset_group, observed_points, or expected_points) cause row-level errors
- Invalid date format (not YYYY-MM-DD) triggers validation failure
- Minimum value greater than maximum value may produce empty interval filter results
- Non-numeric values in observed_points or expected_points fields cause parsing errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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