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Data Reconciliation: String Normalisation + Equal-Width Histogram
x402
Data Reconciliation: String Normalisation + Equal-Width Histogram 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).
Runs two local analytical reports on reconciliation data: string normalisation of row fields and an equal-width histogram over a chosen numeric column (source_total or target_total), for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram 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: (1) a string normalization report cleaning row_id, dataset_group, and date fields across all submitted rows, and (2) an equal-width histogram report showing bin edges, counts, and frequency distribution for the selected numeric column (source_total or target_total), across up to 200 rows. No external lookups or predictions are made.
Example use cases
Auditing financial reconciliation spread
“I've got 120 rows of daily source and target totals for our finance reconciliation — can you run a 5-bin histogram on source_total and normalize all the string fields so I can see how the values are distributed?”
Spotting label inconsistencies in grouped data
“My reconciliation export has messy dataset_group and row_id labels across 80 rows — normalize the strings and give me an equal-width histogram of target_total with 8 bins so I can spot any outliers.”
Cross-group distribution check for two totals
“For these 30 reconciliation records split across group-a and group-b from Q4 2026, run the string normalization and a 5-bin histogram on source_total so I can see if the groups have similar distributions.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-031?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local analytical processing of reconciliation data combining string normalization with histogram analysis in a single call. Ideal when you have up to 200 rows of source/target reconciliation records and want both data quality cleanup and a frequency distribution summary without any external lookups, live predictions, or professional assessments. Good value when you need two distinct reports for a flat $0.01 USDC fee.
Side effects
- Rows array empty or missing — validation error returned
- More than 200 rows submitted — rejected with maxItems error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- bin count outside 1–30 range — rejected with min/max constraint error
- source_total or target_total values outside ±1,000,000,000,000 — rejected
- field value not one of 'source_total' or 'target_total' — enum validation error
- Missing required row fields (row_id, dataset_group, date) — validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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