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Null Coverage Analytics — String Normalisation & Category Frequencies
x402
Null Coverage Analytics — String Normalisation & Category Frequencies 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 string normalization and category frequency reports for up to 200 rows of supplied data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — String normalisation + Category frequencies: String normalisation + Category frequencies 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 analytical reports: (1) a string normalization report that standardizes and cleans the dataset_group and other string fields across the supplied rows, and (2) a category frequency report showing how often each dataset_group appears and the distribution of missing/total values across categories. Both reports are computed locally from the submitted data with no external lookups.
Example use cases
Data Quality Audit by Dataset Group
“I've got 50 rows of data completeness records across groups like 'customer-data', 'transactions', and 'events' with dates and missing/total value counts — can you give me a category frequency breakdown and normalized group labels so I can see which datasets have the worst null coverage?”
Monthly Missing Value Pattern Review
“I have 120 rows of null coverage records spanning October and November 2026 across 5 dataset groups. Can you run string normalization and category frequency analysis on them so I can spot which groups and dates have the most consistent missing value problems?”
Pre-Pipeline Data Completeness Check
“Before I run my ETL pipeline, I want to check my 80 source records for null coverage — each row has a group name, date, and missing vs total value counts. Can you normalize the group strings and give me category frequencies so I know what I'm working with?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-024?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalization and category frequency analysis on null/missing-value records in a single low-cost call. It is ideal for data quality auditing workflows where you have up to 200 rows of structured coverage data with dataset group labels, dates, and missing/total value counts, and you want offline, local analytics without any external lookup or prediction.
Side effects
- Submitting more than 200 rows returns a validation error
- Rows missing required fields (row_id, dataset_group, date, missing_values, total_values) will be rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected
- Empty rows array (minItems: 1 not met) returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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