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Data Reconciliation — Numeric Row Ordering + Explicit Missing-Value Fill
x402
Data Reconciliation — Numeric Row Ordering + Explicit 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 2026-10-19).
Sorts reconciliation rows numerically and fills missing source_total or target_total values using zero, mean, or median imputation for up to 200 records, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied data reconciliation records (source_total, target_total). 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 independent analytical reports covering up to 200 reconciliation rows: one with rows sorted in numeric order, and one with missing values in the specified field (source_total or target_total) filled using the chosen method (zero, mean, or median). No external lookups or predictions are made — all computation uses the supplied data only.
Example use cases
Impute missing source totals for monthly close
“I'm doing a month-end reconciliation and several of my source_total fields are null. Can you fill in those missing source_total values using median imputation and return the rows in numeric order? I'll send you up to 80 rows with row_id, dataset_group, date, source_total, and target_total.”
Clean target totals before audit review
“Before our audit, I need to fill any missing target_total entries in my reconciliation file using zero fill, then sort all the rows numerically. I have around 120 rows across two dataset groups — can you run that for me?”
Mean-fill reconciliation data for dashboard
“My dashboard pipeline has gaps in the target_total column across about 30 reconciliation records. Can you apply mean imputation to those missing target_total values and order the rows numerically so I can load them cleanly?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-124?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both numeric ordering and missing-value imputation applied to reconciliation data in a single call, with results delivered as two independent local reports. It is well-suited for financial or accounting reconciliation workflows where source and target totals need cleaning before comparison or audit, and no external data sources or predictions are required.
Side effects
- More than 200 rows submitted — exceeds maximum row limit
- Invalid date format not matching YYYY-MM-DD pattern
- source_total or target_total values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)
- Missing required fields (row_id, dataset_group, date) on any row
- Invalid enum value for field or method parameters
- Empty rows array submitted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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