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Null Coverage Daily Sum Series + Keyed Dataset Comparison
x402
Null Coverage Daily Sum Series + 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).
Analyzes null/missing value coverage records by producing a daily sum time series and a keyed dataset comparison across up to 200 rows in two independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Daily sum series + Keyed dataset comparison: Daily sum series + 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 analytical reports: (1) a daily sum time series aggregating the selected field (missing_values or total_values) by date, and (2) a keyed dataset comparison highlighting differences between the primary and secondary supplied datasets, both computed locally without external lookups.
Example use cases
Daily missing value trend report
“I have two months of data quality records with date, row_id, dataset_group, missing_values, and total_values. Can you generate a daily sum series for missing_values so I can see which days had the worst null coverage?”
Dataset version null coverage diff
“I have two versions of my dataset — each with row_id, date, dataset_group, missing_values, and total_values — can you compare them and tell me where the null coverage differs between the two?”
Total values aggregation by date
“Here are my 150 records with row_id, date, dataset_group, missing_values, and total_values. Can you run the daily sum series report on total_values and also compare it against my reference dataset to highlight discrepancies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-144?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline, deterministic null/missing value analysis on supplied tabular data — specifically when you want both a time-series daily sum and a side-by-side keyed comparison between two datasets in a single call. It is ideal for data quality audits, ETL pipeline monitoring, and completeness checks where no external data lookups or predictions are needed.
Side effects
- Missing required fields (row_id, date, missing_values, total_values) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Exceeding 200 rows in either dataset returns an error
- Null or out-of-range numeric values outside ±1,000,000,000,000 may be rejected
- Empty rows array (minItems:1 violated) returns a schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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