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Trade Observations — Adjacent Row Changes + Explicit Missing-Value Fill
x402
Trade Observations — Adjacent Row Changes + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Computes adjacent-row delta changes and fills missing values (export_amount or import_amount) in trade observation records using zero, mean, or median imputation.
Price / call$0.01
Success—
StatusUnknown
How this service works
Trade observations — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied trade observations records (export_amount, import_amount). 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
Two analytical reports: (1) an adjacent-row change report showing value deltas between consecutive rows for the specified field (export_amount or import_amount), and (2) an explicit missing-value fill report showing which null entries were replaced and with what imputed value (zero, mean, or median), covering up to 200 input rows.
Example use cases
Fill missing import values in trade dataset
“I've got a table of regional trade observations where some import_amount entries are null — can you fill those in using the mean of the other values and also give me the row-to-row change report for import_amount? I have about 120 rows with row_id, region, date, export_amount, and import_amount.”
Detect export amount shifts between dates
“Can you analyze my trade data and tell me how export_amount changes from one row to the next across all my regions? I also want any missing export_amount fields filled using zero. I have 80 rows with row_id, region, date, export_amount, and import_amount.”
Clean sparse trade records for downstream analysis
“My trade observations dataset has gaps in export_amount and I need two things: a report on adjacent row changes in export_amount, and those missing values filled using median imputation. There are about 150 rows covering multiple regions and dates.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-06-162?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular trade data (export/import amounts) and need both row-to-row delta analysis and missing-value imputation in a single call, without requiring external data, predictions, or live lookups. Ideal for offline data cleaning and exploratory economic analysis pipelines on datasets up to 200 rows.
Side effects
- Exceeds 200-row limit — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Missing required field (row_id, region, date) — validation failure
- Values outside ±1,000,000,000,000 range — rejected by schema
- Invalid method enum value — schema validation error
- Empty rows array — minItems constraint violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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