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Null Coverage String Normalisation and Keyed Dataset Comparison
x402
Null Coverage String Normalisation and 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 2026-10-18).
Analyzes null/missing value coverage across two supplied datasets (up to 200 rows each) using string normalization and keyed group comparison, producing two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — String normalisation + Keyed dataset comparison: String normalisation + 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
Two independent null coverage analytical reports derived from the two supplied row arrays, including string-normalized group key comparisons, missing value counts, total value counts, and coverage statistics per group and date. No external lookups or predictions are made — all analysis is performed locally on the supplied data.
Example use cases
Pipeline completeness audit between runs
“I have two daily pipeline exports, each with around 150 rows tagged by dataset group and date, and I want to see a null coverage report for each and a keyed comparison showing which groups got worse or better between the two runs — here are both arrays of rows with their row_id, dataset_group, date, missing_values, and total_values.”
Data quality regression check after ETL change
“We just updated our ETL process and I need to compare null coverage before and after — I have two datasets of up to 200 rows each with group labels, dates, missing value counts, and total value counts. Can you normalize the group keys and give me a side-by-side comparison of missing value rates?”
Multi-group coverage monitoring for reporting
“I need to audit two batches of our monthly reporting data — each batch has rows with a row ID, a dataset group, a date, and counts of missing and total values — please analyze null coverage across both batches and tell me which groups have the highest proportion of missing values in each.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two structured datasets with explicit null/missing value counts per row and want a normalized, keyed group comparison without any external data fetching, live lookup, or ML prediction. Ideal for data quality audits, pipeline regression checks, and completeness reporting on supplied data up to 200 rows per dataset.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) in any row — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected
- Empty rows array (minItems: 1 not met) — error returned
- Payment of 0.01 USDC not included or fails — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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