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Time Series Completeness: Two-Measure Correlation + Secondary Weighted Mean
x402
Time Series Completeness: Two-Measure Correlation + Secondary 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 2026-10-23).
Computes two-measure correlation and secondary-measure weighted mean analytics for time series completeness records (observed vs expected data points), processing up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Two-measure correlation + Secondary-measure weighted mean: Two-measure correlation + 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 for the submitted time series completeness data: (1) a two-measure correlation report showing the statistical relationship between observed_points and expected_points across rows, and (2) a secondary-measure weighted mean report for the selected field (observed_points or expected_points). Both reports use local analytical engines with no external data lookup.
Example use cases
Data pipeline completeness audit
“I've got 90 rows of daily completeness records for my data pipeline — each row has an observed_points and expected_points count per dataset group and date. Can you compute the two-measure correlation and weighted mean on the observed_points field so I can see how consistent my pipeline has been?”
Monitoring sensor coverage analysis
“Here are 120 rows of sensor coverage data showing expected vs observed readings per day and sensor group. Run the correlation and secondary weighted mean analysis on expected_points so I understand how well coverage targets are being met.”
Reporting dataset quality check
“I need to statistically validate 40 rows of reporting completeness data across two dataset groups — each row has a date, observed_points, and expected_points. Can you get me the two-measure correlation and weighted mean for observed_points?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-181?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline statistical computation of correlation and weighted mean for time series completeness data (observed vs expected point counts) without requiring any external lookups or predictions. Ideal for data quality pipelines, monitoring dashboards, or reporting workflows that need two bundled analytical outputs in a single low-cost call for up to 200 rows.
Side effects
- More than 200 rows submitted — request rejected at input validation
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- Date field not in YYYY-MM-DD format — pattern validation failure
- Null values in numeric fields may affect correlation computation
- Invalid field enum value (not observed_points or expected_points) — rejected
- Payment not included or insufficient USDC — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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