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Record Routing Analytics: Category Frequencies + Missing-Value Fill
x402
Record Routing Analytics: Category Frequencies + Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Computes category frequencies and fills missing values (zero/mean/median) for accepted_records and rejected_records fields across up to 200 record routing rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Category frequencies + Explicit missing-value fill: Category frequencies + Explicit missing-value fill for supplied record routing records (accepted_records, rejected_records). 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) category frequency counts for the dataset_group column across all supplied rows, and (2) the specified numeric field (accepted_records or rejected_records) with missing values filled using the chosen method (zero, mean, or median). No external lookups or predictions are made — all analysis runs locally on the supplied data.
Example use cases
Audit record routing pipeline quality
“I have 120 rows of record routing logs with accepted_records and rejected_records per dataset group. Can you compute the category frequencies across all groups and fill any missing accepted_records values with the median so I can see where nulls are hiding?”
Zero-fill rejected records for reporting
“My weekly record routing export has some null values in the rejected_records column — can you fill those with zero and also give me a frequency breakdown of how many rows belong to each dataset_group?”
Detect imbalanced routing groups
“I want to understand if certain dataset groups dominate my record routing data. Can you run a category frequency report on my 80 routing rows and also use mean imputation to fill any gaps in the accepted_records field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-112?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local statistical analysis on record routing data — specifically category frequency distributions and missing-value imputation — without any external API calls, ML predictions, or live data lookups. Ideal for data quality checks on small-to-medium batches (up to 200 rows) at very low cost ($0.01 USDC for both reports).
Side effects
- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — rejected with maxItems error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Field value out of allowed numeric range (±1 trillion) — rejected
- Invalid method enum value — schema error
- Invalid field enum value — schema error
- All values in target field are null — mean/median may return zero or undefined
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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