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Data Reconciliation — Equal-Width Histogram + IQR Outlier Flags
x402
Data Reconciliation — Equal-Width Histogram + IQR Outlier Flags 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 IQR-based outlier flags for source_total or target_total fields across up to 200 data reconciliation records, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Equal-width histogram + IQR outlier flags: Equal-width histogram + IQR outlier flags 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: (1) an equal-width histogram showing how values are distributed across the specified number of bins, and (2) a list of rows flagged as outliers based on the interquartile range (IQR) method — all computed locally without external lookups or predictions.
Example use cases
Detect outliers in financial reconciliation
“I have 120 daily reconciliation records with source_total and target_total values — can you build an equal-width histogram with 8 bins and flag any IQR outliers on the source_total field so I can see which rows are anomalies?”
Audit target totals across dataset groups
“Here are 80 reconciliation rows across two dataset groups. Can you analyze the target_total field using 5 bins and IQR outlier detection so I can see if any groups have unusually high or low values?”
QA pipeline data before monthly close
“Before we close the books, I need to check these 200 reconciliation records for distributional anomalies — run the equal-width histogram with 10 bins and IQR outlier flags on source_total so I can spot anything out of range.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-170?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical analysis of reconciliation data — specifically equal-width histogram binning combined with IQR outlier detection — on datasets up to 200 rows, without requiring external data lookups, predictions, or professional assessments. It is ideal for data quality checks, pre-close audits, and anomaly detection on source/target financial totals.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row validation failure
- Missing required fields (row_id, source_total, target_total, dataset_group, date) causes schema error
- bin count outside 1–30 range returns validation error
- null values in the selected numeric field may affect IQR computation
- Malformed JSON body returns 400 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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