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Time Series Completeness Analytics — Category Frequencies + Two-Measure Correlation
x402
Time Series Completeness Analytics — Category Frequencies + Two-Measure Correlation 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 (observed vs expected data points) to produce two reports: category frequency distribution by dataset group and correlation analysis between observed_points and expected_points.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation 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 category frequency table showing how often each dataset_group appears in the supplied rows, and (2) a two-measure correlation report quantifying the statistical relationship between observed_points and expected_points across all rows. Both reports are computed locally from the supplied data without any external lookups.
Example use cases
Data pipeline completeness audit
“I have daily completeness records for two data pipelines — 'pipeline-alpha' and 'pipeline-beta' — for the past 6 months, with observed and expected point counts per day. Can you give me a frequency breakdown by pipeline group and tell me how correlated the observed points are to the expected points across all rows?”
IoT sensor coverage monitoring
“I'm tracking IoT sensor coverage across 'zone-north' and 'zone-south' sensor groups. I've got up to 150 rows of daily records with observed vs expected readings. Run a category frequency report and a correlation between observed and expected readings for me.”
ETL job completeness review
“We run nightly ETL jobs across three groups — 'batch-a', 'batch-b', and 'batch-c' — and I've recorded the observed vs expected data points for each day this quarter. Can you analyze how frequently each group appears and whether observed points are correlated with expected points?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-108?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of time series completeness records with observed and expected point counts and need both a categorical frequency summary and a correlation analysis in a single low-cost call ($0.01 USDC). It is ideal for lightweight, self-contained statistical reporting on data quality metrics without requiring external data sources, predictions, or professional assessment services.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, date, observed_points, expected_points) cause validation errors
- Dates not matching YYYY-MM-DD pattern fail schema validation
- Null values in observed_points or expected_points may affect correlation computation
- Fewer than 2 rows may produce degenerate or undefined correlation results
- Payment of 0.01 USDC not completed — x402 payment required before response is returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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