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Agricultural Output — Record Quality Audit + Two-Measure Correlation
x402
Agricultural Output — Record Quality Audit + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Audits data quality and computes Pearson correlation between output_tonnes and cultivated_hectares for up to 200 agricultural output rows, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Agricultural output — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied agricultural output records (output_tonnes, cultivated_hectares). 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) a record quality audit flagging issues such as missing values, nulls, out-of-range numbers, and format errors across all submitted rows; and (2) a two-measure correlation report computing the statistical relationship (e.g. Pearson r) between output_tonnes and cultivated_hectares across the dataset. Both reports are derived entirely from the supplied data with no external lookups.
Example use cases
Farm yield data quality check
“I've got 120 rows of regional harvest data with output_tonnes and cultivated_hectares for 2024. Can you audit them for quality issues like missing values, nulls, or out-of-range numbers, and also tell me if there's a correlation between how much land was farmed and how much was produced?”
Agri-economics dashboard validation
“Before I publish my agricultural economics dashboard, can you run a quality audit on my 80 crop output records dated between 2025-03-01 and 2025-09-30 and compute the correlation between output_tonnes and cultivated_hectares to make sure the data makes sense?”
Comparing two regional farming groups
“I have two groups of records — 'group-a' and 'group-b' — each with about 40 rows of farm output data. Can you audit the data quality across all 80 rows and check whether there's a statistically meaningful correlation between cultivated hectares and tonnes produced?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-16-015?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a two-measure statistical correlation on agricultural output records (output_tonnes vs cultivated_hectares) in a single cheap call ($0.01 USDC for up to 200 rows). It is ideal for pre-publication data validation, exploratory data quality checks, and quick statistical sanity checks on farm or crop datasets without needing an external analytics platform. Prefer this over generic statistics APIs when your data is specifically structured around regional agricultural output with row-level identifiers and date-stamped entries.
Side effects
- Empty rows array or fewer than 1 row returns a validation error
- More than 200 rows exceeds the maximum and will be rejected
- Rows missing required fields (row_id, region, date, output_tonnes, cultivated_hectares) cause schema validation failure
- Malformed date strings not matching YYYY-MM-DD pattern trigger format errors
- Completely null numeric columns may produce undefined or degenerate correlation results
- Payment not supplied or insufficient USDC causes 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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