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Null Coverage Analytics: Adjacent Row Changes + Two-Measure Correlation
x402
Null Coverage Analytics: Adjacent Row Changes + 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 2026-10-14).
Analyzes null coverage records by computing adjacent row changes and two-measure correlation across up to 200 rows of missing_values and total_values data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation for supplied null coverage records (missing_values, total_values). 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
Two analytical reports computed from the supplied rows: (1) an adjacent row changes report showing how the selected measure shifts between consecutive rows, and (2) a two-measure correlation report quantifying the statistical relationship between missing_values and total_values — all derived locally from the supplied data with no external lookups.
Example use cases
Daily data pipeline quality audit
“I have 50 rows of daily pipeline data with missing_values and total_values per dataset group. Can you analyze how missing_values change between consecutive rows and also check whether missing_values and total_values are correlated across these records?”
Detecting null spikes across dataset groups
“Run adjacent row changes and a two-measure correlation on my null coverage records for groups A and B from last quarter — I want to see if missing_values are spiking in specific rows and how strongly they track with total_values.”
Pre-release data completeness check
“Before we ship this dataset, can you compute adjacent row changes and the correlation between missing_values and total_values across these 120 records to make sure our null coverage looks stable and the two measures are behaving consistently?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-158?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two specific analytical views — sequential row change detection and two-measure correlation — on null coverage data (missing_values, total_values) without any external data fetching or prediction. It is best for data quality auditing pipelines, pre-release completeness checks, or ongoing monitoring of dataset null rates, especially when you want both analyses bundled in a single low-cost call.
Side effects
- Fewer than 1 or more than 200 rows supplied — request rejected
- Missing required fields (row_id, date, dataset_group, missing_values, total_values) in any row — validation error
- Date not matching YYYY-MM-DD format — schema validation failure
- Null values in both measure fields making correlation undefined — degenerate result
- Non-numeric values for missing_values or total_values — type error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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