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Elevation Samples — String Normalisation + Adjacent Row Changes
x402
Elevation Samples — String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Analyzes elevation sample records by normalising string fields and detecting adjacent row changes for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Elevation samples — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied elevation samples records (elevation_m, 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) a string normalisation report covering the station_group and other string fields across all submitted rows, and (2) an adjacent row changes report identifying where consecutive rows differ in the selected numeric field (elevation_m or sample_weight). Both reports are computed locally without external lookups.
Example use cases
Audit elevation station string consistency
“I have 50 elevation sample records from different stations and I want to normalize the station_group strings and see where adjacent rows change — can you run both reports on the elevation_m field for rows like row-1 through row-50 across group-a and group-b?”
Detect consecutive elevation measurement shifts
“Can you analyze these 10 elevation readings and tell me which adjacent rows show changes in elevation_m? I also need the string fields normalized. Here are the records: row-1 group-north 2026-01-01 500m weight 1.5, row-2 group-south 2026-01-02 520m weight 2.0, and so on up to row-10.”
Quality check sample_weight adjacent transitions
“Run string normalization and adjacent row change detection on my elevation sample dataset using sample_weight as the field — I have 20 rows across station groups alpha and beta from 2026-03-01 to 2026-03-20 with weights ranging from 1 to 10.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-13-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have elevation sample tabular data (up to 200 rows) and need both string field normalisation and adjacent row change detection in a single call for $0.01. Prefer this over general-purpose data tools when your data specifically contains elevation_m and sample_weight columns with station_group identifiers, and you want two bundled reports without external API dependencies or live lookups.
Side effects
- Exceeding 200 rows returns a validation error
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Missing required fields (row_id, station_group, date, elevation_m, sample_weight) returns an error
- Null values for both numeric fields may limit adjacent-change analysis
- Field enum value outside 'elevation_m' or 'sample_weight' is rejected
- Payment failure via x402 protocol blocks the request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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