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Sampling Observations — Adjacent Row Changes + Date-by-Category Pivot
x402
Sampling Observations — Adjacent Row Changes + Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Runs two local analytical reports on supplied sampling observation rows: an adjacent-row change analysis and a date-by-category pivot table.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Adjacent row changes + Date by category pivot: Adjacent row changes + Date by category pivot for supplied sampling observations records (sample_value, sample_weight). 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) an adjacent row changes table showing value deltas between consecutive rows for the selected field, and (2) a date-by-category pivot table summarizing the selected field (sample_value or sample_weight) across dataset groups and dates. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Tracking sensor reading drift over time
“I have 150 daily sensor readings tagged with group labels, dates, and sample values — run the adjacent row change report and the date-by-category pivot on sample_value so I can see where readings are drifting between consecutive measurements.”
Quality control across production batches
“Here are 80 sampling records from two production groups with dates and measured values — give me the adjacent row change analysis and the date-by-group pivot table for sample_value so I can spot batch-to-batch anomalies.”
Survey response weight analysis by cohort
“I've got 120 survey response rows, each with a date, a cohort group, a response score as sample_value, and a sample_weight — can you produce both the adjacent-row change report and the date-by-category pivot using sample_weight so I can compare cohort weightings over time?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-160?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a sequential change analysis and a cross-tabulated date-by-category pivot in one call for up to 200 sampling observation records containing numeric values and group labels. It is ideal for batch offline analysis of structured tabular data where no external data, predictions, or live lookups are needed. Particularly suited for survey data, sensor readings, or quality-control samples organized by group and date.
Side effects
- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — request rejected
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) — schema validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Numeric values outside ±1,000,000,000,000 range — validation error
- Invalid field enum value (not sample_value or sample_weight) — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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