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Field Survey Coverage — Keyed Dataset Comparison + Explicit Missing-Value Fill
x402
Field Survey Coverage — Keyed Dataset Comparison + 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 2026-10-29).
Compares two keyed field survey coverage datasets (surveyed_m2, target_m2) row by row and fills missing values explicitly, producing two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Field survey coverage — Keyed dataset comparison + Explicit missing-value fill: Keyed dataset comparison + Explicit missing-value fill for supplied field survey coverage records (surveyed_m2, target_m2). 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) a keyed dataset comparison showing row-by-row differences between the primary and secondary survey coverage datasets for the selected field, and (2) an explicit missing-value fill report showing which rows had null values and what they were replaced with. Both reports cover up to 200 rows and are produced using local analytical engines with no external lookups.
Example use cases
Reconciling two survey coverage snapshots
“I have two versions of our field survey coverage data for October 2026 across station groups A and B — each with row IDs, dates, surveyed_m2, and target_m2. Can you compare them row by row and flag where the surveyed_m2 values differ, and fill in any nulls?”
Auditing missing target area values
“My field survey dataset has some null target_m2 entries across about 150 rows. Can you run the explicit missing-value fill on the target_m2 field and give me back the two audit reports showing what was filled?”
Station group coverage gap analysis
“We ran two independent surveys of the same sites last month — I need to compare surveyed_m2 across both datasets keyed by row_id and station_group, and fill any gaps, so I can see where coverage fell short of target.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-22-190?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two structured field survey coverage datasets with keyed rows (row_id, station_group, date) and need both a side-by-side comparison of surveyed_m2 or target_m2 values AND explicit null-filling in a single $0.01 call. It is ideal for data quality workflows on moderate-sized survey datasets (up to 200 rows) where no live data lookup or external prediction is needed — purely local analytical computation on supplied data.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, station_group, date) in any row — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — validation failure
- Empty rows array — minItems constraint violation
- Invalid field enum value (not surveyed_m2 or target_m2) — enum validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array | |
| method | string |
Tags
x402
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