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Null Coverage Dual Analytics: Two-Measure Correlation + Keyed Dataset Comparison
x402
Null Coverage Dual Analytics: 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 2026-10-14).
Computes correlation between missing_values and total_values, and compares two null-coverage datasets by shared row keys — returning two analytical reports for up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Two-measure correlation + Keyed dataset comparison: Two-measure correlation + Keyed dataset comparison 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
Returns two independent analytical reports: (1) a two-measure Pearson or rank correlation between missing_values and total_values across all supplied rows, and (2) a keyed dataset comparison aligning rows from the primary and secondary datasets by row_id and reporting differences in null coverage metrics. Both reports are computed locally with no external lookups.
Example use cases
Data pipeline null rate audit
“I'm auditing my ETL pipeline's output quality. I have 150 rows of null coverage data from last week's run, each tagged with a row_id, dataset_group, date, missing_values, and total_values. Can you correlate missing_values with total_values to see if larger datasets are missing more data, and also compare them against this week's 150 rows by row key to find where null coverage has changed?”
Schema migration quality comparison
“We just migrated our database schema and I need to verify data completeness didn't regress. I have pre-migration and post-migration null coverage records — both with row_id, dataset_group, date, missing_values, and total_values, about 80 rows each. Please correlate missing_values against total_values in the pre-migration set and compare both datasets row-by-row to flag where null counts shifted.”
Multi-group null coverage correlation
“I'm analyzing null coverage across two dataset groups — 'group-a' and 'group-b' — over the past month. I have 120 rows with row_id, dataset_group, date, missing_values, and total_values. Can you compute the correlation between missing_values and total_values across all rows, and then compare this month's records against last month's keyed dataset to see which row IDs show the biggest changes in null coverage?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-183?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a statistical correlation between two null-coverage measures and a row-keyed comparison between two dataset snapshots in a single paid call. It is ideal for data quality workflows where you want to understand the relationship between missingness and dataset size while simultaneously diffing two versions of the same dataset. It does not perform live data lookups, predictions, or external enrichment — use it purely for local analytical computation on supplied null coverage records.
Side effects
- Fewer than 1 row supplied — minimum item count not met
- More than 200 rows supplied — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) on any row
- date field not matching YYYY-MM-DD pattern
- row_id exceeds 80-character maxLength
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)
- Correlation undefined if all missing_values or total_values are identical (zero variance)
- Payment failure — 0.01 USDC not settled via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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