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Tree Canopy Observations — Record Quality Audit + Exact Row Deduplication + Equal-Width Histogram
x402
Tree Canopy Observations — Record Quality Audit + Exact Row Deduplication + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Runs three analytical reports on tree canopy observation records: a data quality audit, exact row deduplication, and an equal-width histogram over canopy_m2 or plot_m2 values.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tree canopy observations — Record quality audit + Exact row deduplication + Equal-width histogram: Record quality audit + Exact row deduplication + Equal-width histogram for supplied tree canopy observations records (canopy_m2, plot_m2). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports: (1) a record quality audit flagging missing, null, or out-of-range values for each row; (2) a list of exact duplicate rows identified in the dataset; (3) an equal-width histogram of the selected numeric field (canopy_m2 or plot_m2) with the specified number of bins and per-bin counts.
Example use cases
Pre-analysis data quality check
“I have 120 tree canopy survey records with canopy_m2 and plot_m2 measurements across several station groups — can you run a quality audit on them, find any exact duplicate rows, and show me a 5-bin histogram of canopy_m2 so I know the data is clean before I start modeling?”
Distribution check on plot sizes
“Before I aggregate my canopy plots, can you deduplicate my 80 observation records and generate a 10-bin equal-width histogram of the plot_m2 field so I can see how plot sizes are distributed?”
Field data validation for reporting
“I just collected 150 tree canopy records from the field and need to validate them — please run a record quality audit, strip out any exact duplicates, and histogram the canopy_m2 values into 8 equal-width bins so I can include the summary in my report.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-219?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 tree canopy observation records and need all three reports — quality audit, deduplication, and histogram — in a single low-cost call. It is ideal for pre-processing field survey data before downstream modeling or reporting, and requires no external connectivity or live data sources. Not suitable for real-time sensor streams, large datasets over 200 rows, or predictive modeling tasks.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required row fields (row_id, date, canopy_m2, plot_m2, station_group) — validation error
- Invalid date format (non-YYYY-MM-DD) — schema rejection
- Bins value outside 1–30 range — parameter error
- Payment not included or insufficient — x402 payment required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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