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Tree Canopy Observations — Grouped Numeric Summary + Missing-Value Fill
x402
Tree Canopy Observations — Grouped Numeric Summary + 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 grouped numeric summaries and fills missing values (canopy_m2, plot_m2) for up to 200 tree canopy observation records using two local analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tree canopy observations — Grouped numeric summary + Explicit missing-value fill: Grouped numeric summary + Explicit missing-value fill for supplied tree canopy observations records (canopy_m2, plot_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 per call: (1) a grouped numeric summary of the selected field (canopy_m2 or plot_m2) broken down by station_group, and (2) the same records with missing values in the selected field explicitly filled using the chosen method (zero, mean, or median). Results are computed locally without external lookups.
Example use cases
Urban forest coverage analysis by district
“I have 50 tree canopy measurements from different monitoring stations across the city — can you group them by station_group and summarize the canopy_m2 statistics, using median to fill any missing values?”
Plot size data cleaning before modeling
“Before I run my model I need to fill nulls in my plot_m2 field using zero fill and get a grouped summary — I have about 120 rows with row_id, date, station_group, canopy_m2, and plot_m2.”
Comparing canopy coverage across research sites
“Can you aggregate these 80 tree canopy observation records by station group and give me a numeric summary of the canopy_m2 measurements? Use mean imputation for any missing canopy values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-099?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular tree canopy or plot observation data that needs grouped aggregation and missing-value imputation in a single call. It is ideal for forestry, environmental, or urban ecology datasets where station-group-level summaries and null handling are needed before downstream analysis, and where no external data lookup or predictive modeling is required.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, station_group, date, canopy_m2, plot_m2) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Numeric values outside the allowed range (±1,000,000,000,000) are rejected
- Unsupported method or field enum values cause schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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