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Numeric Precision Comparisons — Adjacent Row Changes + Secondary-Measure Weighted Mean
x402
Numeric Precision Comparisons — Adjacent Row Changes + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Computes adjacent row-to-row changes and a secondary-measure weighted mean for up to 200 rows of numeric precision comparison data (source_value vs. transformed_value).
Price / call$0.01
Success—
StatusUnknown
How this service works
Numeric precision comparisons — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean for supplied numeric precision comparisons records (source_value, transformed_value). 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) adjacent row changes showing the difference between consecutive source_value or transformed_value entries per the selected field, and (2) a secondary-measure weighted mean that uses one numeric column to weight the average of another — all computed locally on the supplied data without external lookups.
Example use cases
ETL pipeline accuracy audit
“I've exported 150 rows from our ETL pipeline with source_value and transformed_value columns, grouped by dataset_group and dated — can you calculate the adjacent row changes and weighted mean for source_value so I can see where the largest precision shifts are happening?”
Financial data transformation review
“Here are 80 rows of financial records comparing raw and processed numeric values, each with a date and group label — please run the adjacent row changes report and secondary-measure weighted mean on transformed_value so I can validate the transformation accuracy.”
Sensor reading conversion analysis
“I have 60 sensor readings before and after unit conversion, stored as source_value and transformed_value, grouped by sensor type — give me the row-to-row changes and a weighted mean report on source_value to check for anomalies in the conversion.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-20-159?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two specific offline statistical analyses — adjacent row changes and weighted mean — on numeric source-vs-transformed comparison data in a single call. It is ideal for data quality audits, ETL validation, and transformation accuracy checks where no live data lookup or external enrichment is needed. Prefer it over generic analytics services when your data fits the precision-comparison schema (source_value + transformed_value per row) and you want a cost-effective bundled report ($0.01 for both analyses).
Side effects
- Input rows array is empty or exceeds 200 items — rejected with validation error
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) on any row — rejected
- Date field does not match YYYY-MM-DD pattern — validation error
- Numeric values outside [-1000000000000, 1000000000000] range — rejected
- Invalid field enum value (must be source_value or transformed_value) — rejected
- All values null for the selected field — weighted mean may be undefined or zero
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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