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Data Reconciliation — Equal-Width Histogram + Explicit Missing-Value Fill
x402
Data Reconciliation — Equal-Width Histogram + 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).
Generates an equal-width histogram and fills missing values (zero/mean/median) for source_total and target_total reconciliation data across up to 200 rows, producing 2 analytical reports locally.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Equal-width histogram + Explicit missing-value fill: Equal-width histogram + 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 2 analytical reports: (1) an equal-width histogram of the specified field (source_total or target_total) divided into the requested number of bins, showing frequency distribution; (2) a missing-value fill report where nulls in the specified field are replaced using the chosen method (zero, mean, or median), applied to up to 200 input reconciliation rows. All computation is local with no external lookups.
Example use cases
Reconciling monthly ledger discrepancies
“I've got 80 rows of monthly ledger data with source_total and target_total fields — a few source_total entries are null. Can you fill those nulls with the median and then give me a 10-bin histogram of source_total so I can see the distribution?”
Auditing ETL pipeline output gaps
“Our ETL pipeline produced 120 reconciliation records across two dataset groups and some target_total values are missing. Fill those gaps using zero and generate a 5-bin equal-width histogram on target_total so I can audit the spread.”
Pre-analysis data prep for finance team
“Before we hand off these 60 reconciliation rows to the finance team, can you impute any null source_total values using the mean and produce a histogram with 8 bins so they can see how the data is distributed?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-175?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, offline-style analytical report combining histogram bin distribution and missing-value imputation for reconciliation data (source_total vs target_total) without any external data lookups or live predictions. Ideal for pre-analysis data quality checks, audit prep, and distribution visualization for up to 200 rows at very low cost ($0.01 for 2 reports). Prefer this over general BI tools when you want a quick, deterministic local computation on structured reconciliation records.
Side effects
- More than 200 rows submitted — schema enforces maxItems:200, excess rows will be rejected
- Invalid date format (must match YYYY-MM-DD pattern) — returns validation error
- bins value outside 1–30 range — rejected by schema
- source_total or target_total outside ±1,000,000,000,000 — rejected by schema
- Missing required fields (row_id, dataset_group, date) — validation error
- Empty rows array — minItems:1 enforced
- Invalid method enum value — only zero, mean, median accepted
- Invalid field enum — only source_total or target_total accepted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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