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Data Freshness Analytics: Two-Measure Correlation + Date-by-Category Pivot
x402
Data Freshness Analytics: Two-Measure Correlation + Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Runs two local analytical reports on supplied data freshness records — a Pearson/Spearman correlation between age_minutes and record_count, and a date-by-category pivot table — returning both results for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data freshness — Two-measure correlation + Date by category pivot: Two-measure correlation + Date by category pivot for supplied data freshness records (age_minutes, record_count). 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 result (e.g. Pearson/Spearman coefficient and supporting statistics) between age_minutes and record_count, and (2) a date-by-category pivot table summarizing the selected field across dataset_group and date dimensions — both computed locally from the supplied rows with no external lookups.
Example use cases
Pipeline staleness correlation check
“I'm monitoring four data pipelines and have rows with their age in minutes and record counts by date and group — run a correlation between age_minutes and record_count plus give me a date-by-group pivot so I can see which pipelines are going stale.”
Data quality dashboard summary
“I've got freshness logs for our datasets — each row has a date, a dataset_group, age_minutes, and record_count. Can you compute the two-measure correlation and a date-by-category pivot table so I can add both to our data quality dashboard?”
Weekly freshness trend review
“Here are 80 rows of weekly data freshness records across our group-a and group-b datasets with dates from last month — please run the correlation analysis on age_minutes and record_count and also generate a pivot of record_count by date and category.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-06-182?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 data freshness records (age_minutes + record_count) and need both a statistical correlation between those two measures AND a date-by-category pivot in a single low-cost call. It is ideal for pipeline monitoring, data quality dashboards, or freshness audits where you want two complementary views — relational and dimensional — without spinning up a full analytics environment. Prefer it over general-purpose analytics services when cost-per-call matters and the dataset fits the 200-row limit.
Side effects
- Fewer than 1 row supplied — minimum item count not met
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, age_minutes, record_count) — schema validation error
- Invalid date format (must match YYYY-MM-DD pattern) — pattern validation failure
- Non-numeric or out-of-range values for age_minutes or record_count — numeric bounds exceeded
- Invalid enum value for 'field' parameter — must be 'age_minutes' or 'record_count'
- All numeric values are null — insufficient data to compute correlation
- Payment not confirmed — x402 micropayment of 0.01 USDC not completed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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