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Time Series Completeness — Duplicate Key Report + Secondary-Measure Weighted Mean
x402
Time Series Completeness — Duplicate Key Report + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).
Analyzes supplied time series completeness records to produce a duplicate key report and a secondary-measure weighted mean, using shared local analytical engines — no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Duplicate key report + Secondary-measure weighted mean: Duplicate key report + Secondary-measure weighted mean 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 any rows with repeated key combinations, and (2) a weighted mean of the selected secondary measure (observed_points or expected_points) across the supplied rows — computed locally with no external data access, covering up to 200 input rows.
Example use cases
Daily sensor feed completeness audit
“I have daily completeness logs for two sensor groups over the past week — each row has a date, a group name, observed data points, and expected points. Can you check for any duplicate row IDs and compute the weighted mean of observed_points across all rows?”
ETL pipeline data quality check
“After our nightly ETL run I need to validate our completeness table — run a duplicate key report on these 150 rows and also give me the secondary-measure weighted mean using expected_points as the field, so I can spot any anomalies before the morning report.”
Multi-group time series completeness summary
“We track completeness across three dataset groups daily. Here are about 80 rows with row_id, dataset_group, date, observed_points, and expected_points — can you produce both a duplicate key report and a weighted mean of observed_points so I can summarize data quality for my team?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-067?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two simultaneous analytical operations on a batch of time series completeness records — duplicate key detection plus weighted mean computation — without any external data lookups or predictions. Ideal for data quality pipelines, ETL validation, and completeness monitoring workflows where you supply your own data (up to 200 rows) and need fast, local statistical analysis at low cost ($0.01 USDC for both reports).
Side effects
- Input exceeds 200 rows — request rejected
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Null values in numeric fields may affect weighted mean computation
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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