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Transformation Throughput Analytics — Category Frequencies + IQR Outlier Flags
x402
Transformation Throughput Analytics — Category Frequencies + 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 2026-10-28).
Analyzes transformation throughput records to compute category frequencies by dataset_group and flag IQR-based outliers for processed_rows or duration_seconds fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transformation throughput — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags for supplied transformation throughput records (processed_rows, duration_seconds). 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) category frequency counts per dataset_group showing how often each group appears in the supplied records, and (2) IQR-based outlier flags for the specified numeric field (processed_rows or duration_seconds), identifying rows whose values fall outside the interquartile range bounds.
Example use cases
ETL pipeline anomaly detection
“I have 80 transformation job records with row_id, date, dataset_group, processed_rows, and duration_seconds. Can you flag any IQR outliers in duration_seconds and give me the frequency breakdown by dataset_group?”
Data quality audit by group
“Here are my 120 transformation throughput records from last month — compute how often each dataset_group appears and flag any processed_rows values that look like outliers based on IQR.”
Throughput distribution summary
“I want to understand the distribution of my nightly ETL jobs. Please analyze these 40 records and give me category frequencies for dataset_group plus IQR outlier flags for processed_rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-13-107?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both category frequency analysis and IQR outlier detection on transformation throughput records in a single call. It is ideal for ETL pipeline monitoring, data quality audits, and batch statistical summaries of up to 200 rows without requiring any external data lookup or live prediction.
Side effects
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) causes validation error
- Exceeding 200 row limit returns an error or truncation
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- All-null values in the target numeric field may produce empty outlier report
- Non-numeric values in processed_rows or duration_seconds fail schema validation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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