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Data Reconciliation — Daily Sum Series with Missing-Value Fill
x402
Data Reconciliation — Daily Sum Series with 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).
Reconciles daily sum series data between source and target totals, computing daily aggregates and filling missing values using a chosen fill method (zero, mean, or median) for up to 200 rows across two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Daily sum series + Explicit missing-value fill: Daily sum series + 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 analytical reports per call: a daily sum series showing aggregated source_total and target_total by date and dataset group, and an explicit missing-value fill report showing which rows had nulls and what values were substituted using the chosen method (zero, mean, or median). Covers up to 200 input rows with no external lookups or predictions.
Example use cases
ETL pipeline discrepancy audit
“We run a nightly ETL and suspect our target_total is drifting from source_total — can you take these 120 rows of daily records across three dataset groups, fill any nulls in target_total with the mean, and produce the daily sum reconciliation report?”
Financial daily close reconciliation
“Here are 80 rows of daily closing figures for our accounts, with some source_total values missing — reconcile source vs target totals by date, fill the missing source_total entries using zero, and show me the daily sum series breakdown.”
Multi-group data quality check
“I've got two dataset groups — 'north-region' and 'south-region' — with 60 rows of daily totals each; some target_total values are null. Can you fill those with the median and run the daily sum series reconciliation so I can see where they diverge?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-145?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of daily time-series records with source and target totals and need both a daily sum aggregation and explicit missing-value imputation in a single call. It is ideal for ETL validation, data pipeline reconciliation, or financial close audits where you need to compare two data feeds by date and dataset group without any external data lookups. Prefer it over general analytics tools when you need the specific combination of daily sum series plus missing-value fill as paired reports at low per-call cost.
Side effects
- Exceeds 200 row limit — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes validation error
- Missing required fields (row_id, dataset_group, date, source_total, target_total) causes schema rejection
- Values outside ±1,000,000,000,000 range rejected by schema
- Invalid method enum value (not zero/mean/median) causes error
- Invalid field enum value (not source_total/target_total) causes error
- Empty rows array (minItems:1 not met) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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