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Null Coverage Analyzer — Numeric Row Ordering & Date-by-Category Pivot
x402
Null Coverage Analyzer — Numeric Row Ordering & 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 2026-10-16).
Generates two analytical reports on null/missing-value coverage data: a numeric row ordering report and a date-by-category pivot table, for up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot 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 structured analytical reports derived from the supplied rows: (1) a numeric row ordering report ranking rows by the selected field (missing_values or total_values), and (2) a date-by-category pivot table grouping the selected field by date and dataset_group. No external data is fetched; all analysis is performed on the submitted records.
Example use cases
Data quality audit by team pipeline
“I have a batch of up to 150 records from our ETL pipeline, each with a row ID, dataset group name, date, and counts of missing vs total values. Can you rank them by missing_values and also pivot missing_values by date and dataset group so I can see which groups have the worst coverage over time?”
Monthly completeness review across sources
“We track data completeness across several source groups each day. Can you take these 80 records — each with a row_id, dataset_group, date, missing_values, and total_values — and produce a numeric ordering by total_values plus a date-by-category pivot on missing_values so we can spot gaps in our monthly review?”
Debugging sparse data ingestion
“Our ingestion logs show a lot of nulls this week. Here are 60 records with row IDs, group names, dates, and missing vs total value counts — can you sort them numerically by missing_values and pivot by date and category so I can pinpoint which dataset groups and dates are causing the sparsity?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-122?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular null-coverage data (missing_values + total_values per row, group, and date) and need both a ranked row-ordering view and a pivot breakdown by date and category in a single low-cost call. It is purpose-built for data quality and completeness analysis workflows, not for general-purpose pivot or sorting tasks involving other data shapes.
Side effects
- Empty or missing rows array returns a validation error
- Rows exceeding 200 items are rejected (maxItems constraint)
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in missing_values or total_values may affect numeric ordering output
- Invalid field enum value (not 'missing_values' or 'total_values') returns an error
- Missing required fields (row_id, dataset_group, date) cause per-row validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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