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Time Series Completeness: Two-Measure Correlation + Keyed Dataset Comparison
x402
Time Series Completeness: Two-Measure Correlation + 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).
Runs two analytical reports on time series completeness data (observed vs expected points): a correlation analysis between the two measures and a keyed dataset comparison, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Two-measure correlation + Keyed dataset comparison: Two-measure correlation + 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 two-measure correlation analysis between observed_points and expected_points across all supplied rows, and (2) a keyed dataset comparison that matches rows from the primary and secondary datasets by key and reports differences. All analysis is performed locally with no external lookups.
Example use cases
Pipeline completeness drift detection
“I have two months of daily completeness records for my data pipeline — each row has a date, a group name, and observed vs expected point counts. Can you correlate observed with expected and then compare my January dataset against my February dataset row by row to spot where they diverge?”
Cross-environment completeness audit
“We run the same data collection in staging and production. I want to correlate observed_points vs expected_points in our production dataset and also do a keyed comparison between staging and production records to find any mismatches — I have up to 150 rows for each environment.”
Weekly completeness regression check
“Can you check whether observed_points and expected_points are still correlated this week compared to last week? I'll supply both weeks as separate datasets, up to 200 rows combined, with row IDs, groups, and daily dates.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-183?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a statistical correlation between observed and expected data point counts AND a side-by-side keyed comparison of two completeness datasets in a single $0.01 call. Ideal for data quality audits, pipeline completeness checks, and regression comparisons between time periods or environments, when you have up to 200 rows and want two reports without external data fetching.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- Date format not matching YYYY-MM-DD pattern — schema validation failure
- Both datasets empty or missing — no report generated
- Null values in measure fields may affect correlation computation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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